The Competitive Front-of-Package Labeling of Consumer Packaged Goods: Cutting Through The Clutter

At no point in U.S. history have food product packages displayed so many symbols and statements regarding nutrition and health benefits (Nestle 2010). However, despite this explosion of front-of-package (FOP) health communications, obesity and health-related problems of U.S. consumers continue to be a critical concern. Therefore, it is important for marketers, retailers, manufacturers, and public policy makers to develop a more complete understanding of consumers\u27 processing and utilization of health information on food packages, as well as how this information affects product evaluations and choices. Therefore, this dissertation utilizes a processing fluency theoretical framework (e.g., Zajonc 1968; Jacoby and Dallas 1981; Novemsky et al. 2007) to attempt to increase our understanding of how FOP icons that vary in nature (i.e., subjective interpretive icons, objective quantitative icons, single nutrient content claims) affect consumers\u27 perceptions, intentions, and choices when presented both independently and simultaneously on food packages. Study 1 examines reductive and interpretive icons on a single product (pizza), while Study 2 demonstrates how additional FOP nutrition information (i.e., a single nutrient content claim) affects the conceptual fluency of health information, perceived product healthfulness, and purchase intentions. Studies 3 and 4 provide a stronger market-based examination of how consumers process FOP health information across multiple brands and product categories in a retail setting. These controlled retail laboratory studies overcome important limitations noted in earlier nutrition labeling studies, such as data collection and evaluations in non-store environments (e.g., Keller et al. 2007; Li, Miniard, and Barone 2000), while demonstrating how different types of FOP icons vary in their effectiveness in positively affecting consumers\u27 choices of healthy products from consideration sets across multiple food categories