The purpose of this paper is to study the behavioral and lifestyle influences on reported calorie intake. Marketing segmentation techniques applied to self-reported food consumption can offer benefits to both health policy and marketing research.
The two-stage modeling process in this research determines important behavioral, lifestyle and sociodemographic influences on reported calorie intake. Significant predictors are then included in latent class models, which are used to derive and describe five consumer segments.
These segments differ with respect to their food-related activities, such as dieting, grocery shopping and preparing food at home. The segments also differ with respect to lifestyle characteristics, such as household size, employment status and income. Data obtained from a multi-period probability sample help generalize the results to the US population.
The models developed in this paper can inform health policymakers by explaining reported calorie intake patterns more thoroughly than demographics alone, aiding their ability to create more targeted interventions. This approach also allows food marketers to clarify consumer insights that can be used for targeting particular food shopper segments.
The author thanks the editor and reviewers for their constructive feedback. The author also wishes to thank Doug Bowman and Dawn Iacobucci for their helpful comments on earlier drafts of the article.
Popovich, D. (2017), "Behavioral and lifestyle influences on reported calorie intake: a latent class model", Journal of Consumer Marketing, Vol. 34 No. 3, pp. 214-225. https://doi.org/10.1108/JCM-06-2016-1849Download as .RIS
Emerald Publishing Limited
Copyright © 2017, Emerald Publishing Limited