Chapter 2 of this report describes the various types and amounts of product and nutrition information currently found on food packages, including branding, images, claims, and promotions. This chapter examines the effects of such information on consumer preferences and choices, and describes how consumers process information about products when faced with multiple competing stimuli, as found on many food packages today. Findings from this research informed the committee’s recommendations for designing an effective front-of-package (FOP) nutrition labeling system.
Many studies have examined the effects of food package information and marketing on consumer beliefs, preferences, and choices. These studies often use an experimental design in which some element of package labeling is manipulated by the investigators (e.g., present vs. absent). Participants are then exposed to one or several versions of the package, after which they respond in some way to the product(s) they saw. Responses are measured in a host of ways, from survey-based self-reports, to tracking eye movements, to tracking brain activity in neuromarketing studies. Most studies use simulated or computer-generated package stimuli, although some use actual packages, and most occur in controlled settings. Nearly all types of food package information and marketing described in Chapter 2 have been examined in these types of studies.
As Chapters 2 and 3 describe, nutrition-related claims are fairly common on food packages and must adhere to regulatory standards. Such claims therefore provide accurate information about the contents of a product and could conceivably influence some consumers’ attitudes and choices. Manufacturers choose which claims, if any, to make, and presumably this selection process is purposeful, not random. Thus a manufacturer’s choice of claims might influence consumer judgments. For most foods, no single claim would provide a complete characterization of the product as a whole. For example, knowing that a food is a good source of vitamins and iron does not tell consumers whether it is also high or low in saturated fat, sodium, sugar, or calories. Thus when evaluating con-
sumer effects of package claims, it is important to consider not just claim-specific outcomes, but also how claims might affect broader judgments about a product.
In a randomized experiment, Kozup et al. (2003) (Study 1) examined consumer reactions to adding heart-healthy claims to packages of frozen lasagna dinner. Participants were 147 primary food shoppers who completed the study protocol online. Findings showed that those exposed to packages containing the claim reported significantly more favorable nutrition attitudes about the product than those who saw the same package without the label. These attitudes included judging the product to be “nutritious,” “good for your heart,” and “part of a healthy diet.”
Labiner-Wolfe et al. (2010) examined consumer reactions to simulated bread or frozen dinner packages that varied in the presence or absence of nutrition-related claims (“low-carb”) and showing or not showing the Nutrition Facts panel (NFP). Participants in the experiment (n = 4,320) were part of a national online consumer panel. Among participants who saw packages that did not show the NFP, those exposed to packages with “low-carb” claims rated the products as more helpful for weight management and lower in calories than those seeing the identical product with no “low-carb” claim (Labiner-Wolfe et al., 2010). However, when the NFP was present, consumers rated products with and without a “low-carb” claim the same in terms of weight management benefits and calories. This apparent benefit of NFP exposure may have less practical value, though, as the majority of Americans—and an even higher proportion of individuals—do not use the NFP (Guthrie et al., 1995; Morton and Guthrie, 1997; Satia et al., 2005; Blitstein and Evans, 2006; Todd and Variyam, 2008) and thus might be more influenced by claims.
In a study of 320 adults from an online consumer panel, Drewnowski et al. (2010) used conjoint analysis to evaluate reactions to 48 nutrient content and product claims. Claims addressed six nutrients to encourage (protein, vitamin C, vitamin A, fiber, calcium, iron) and five nutrients to avoid (fat, saturated fat, cholesterol, sugar, sodium), and either stated the presence or absence of the nutrient (e.g., “contains calcium” vs. “is rich in calcium”) or the amount of the nutrient (e.g., “good source of vitamin C” vs. “excellent source of vitamin C”). After exposure to each different claim (or group of claims) about a hypothetical product, consumers rated the healthfulness of the product from 1 (least healthy) to 9 (most healthy). Perceptions of healthfulness (ratings of 7-9) were influenced most by claims about the presence of protein and fiber, followed by claims about the absence of saturated fat and sodium, then by claims about the presence of vitamin C and calcium. Claims about nutrients to encourage were more influential on ratings of healthfulness among women than men. The investigators noted the healthfulness ratings were strongly influenced by claims about protein, a nutrient for which there is no shortfall in the American diet, while claims about low or no sugar did little to enhance healthfulness ratings.
Gorton et al. (2010) conducted intercept interviews with 1,525 food shoppers in 25 grocery stores in New Zealand to assess consumer understanding of two package claims—“97 percent fat free” and “no sugar added”—on simulated food packages. Although a large majority of shoppers (72 percent) interpreted these claims correctly, many shoppers also inferred from the claims that the product was healthy. Nearly half of all shoppers (47 percent) said that a food carrying a “97 percent fat free” claim on the package was “definitely a healthy food.” This inference was significantly more likely among shoppers from racial or ethnic minority groups and among low-income shoppers. The same pattern was found for “no sugar added” claims. U.S. studies of responses to nutrition-related claims in food advertising have also found that consumers tend to over-generalize a product’s healthfulness based on narrower claims (Andrews et al., 1998).
In European studies, food products whose packages contain health-related product claims are preferred by consumers over products without such claims (e.g., chosen from a set of options with and without nutrition claims), are viewed as more attractive and elicit greater purchase intentions (e.g., Verbeke et al., 2009; Aschemann-Witzel and Hamm, 2010). The likelihood of choosing a product with a package claim is reduced when consumers have an established habit or history of buying a certain product (Aschemann-Witzel and Hamm, 2010), suggesting that in such instances, the effects of branding and brand loyalty may trump those of nutrition-related claims. Collectively, these findings suggest that (1) nutrition-related claims can influence consumers’ perceptions of a product; (2) these perceptions sometimes exceed the bounds of the claim, extending to generalized beliefs about the healthfulness of the product; and (3) these over-generalizations may be more common among certain subgroups of consumers, including minorities and those with lower income.
The findings of Labiner-Wolfe et al. (2010) suggest that when consumers see not only a label claim, but also a standardized and comprehensive nutrition statement (i.e., the NFP), over-generalizations of a product’s healthful-
ness can be reduced or eliminated. Similarly, Andrews et al. (1998) found that, although consumers over-generalize the healthfulness of products based on specific claims contained in advertising, these over-generalizations can be significantly reduced using evaluative disclosures that specify whether the per serving amount of a nutrient is “high” according to Food and Drug Administration (FDA) criteria. These evaluative disclosures outperformed three other disclosure conditions (no disclosure, absolute disclosure, and relative disclosure) in reducing over-generalizations about a product’s healthfulness, fat content, and benefits for reducing the risks of cancer and heart disease.
It is not clear whether a FOP nutrition label could reduce over-generalizations in the same way that the NFP and evaluative disclosures on advertising did, but evidence of such an effect would provide compelling support for such a system (Schofield and Mullainathan, 2008). In particular, the findings of Andrews et al. (1998) suggest that FOP label formats should evaluate, not just report, amount of key nutrients in a product.
In addition to nutrition-related claims, food packages can also contain branding, promotions, and other product information (see Chapter 2). Product branding used on food packages may also influence consumer preferences. Robinson et al. (2007) examined the effects of marketing and brand exposure on taste preferences of 3- to 5-year-old children from Head Start centers. The children were asked to taste five pairs of identical foods and beverages in various packaging schemes (e.g., boxes, bags, cups) that were either unbranded or branded as “McDonald’s.” Children were significantly more likely to report that the “McDonald’s”-branded food tasted better (Robinson et al., 2007).
Promotional marketing on food packages may also influence consumer preferences and decisions. For example, research shows that a large majority (85 percent) of packaging targeting children uses cartoon-like graphics and typology (Elliott, 2008). To examine the effects of such on-package marketing, Roberto et al. (2010) had children ages 4-6 years taste and rate identical pairs of gummy fruit snacks, graham crackers, and carrots presented in packaging that did or did not include popular cartoon characters. After tasting both, children were also asked to select the product they would choose for a snack. Children preferred the taste of products that came in packages containing a cartoon character (Roberto et al., 2010).
Many studies have examined consumer reactions to value-based labeling. In a large choice experiment, i.e., where participants were asked to choose among products that differ on pre-determined attributes, James et al. (2009) examined consumer preferences for applesauce that varied in label claims and price. Consumers (n = 1,521) recruited from 65 counties in Pennsylvania viewed four sets of four different applesauce labels and were asked to select the one they would choose from each set. All labels included the word “applesauce” and a sales price (that varied by product and set). Some labels also included claims indicating the product was locally grown, organic, low-sugar, or low fat; some labels included combinations of these. Controlling for price, claims that the applesauce was locally grown (“Pennsylvania Preferred”), organic, or low-sugar all increased the likelihood that consumers would choose them (James et al., 2009). Of these, locally grown was by far the strongest predictor of choice. Unexpectedly, applesauce labeled as low fat was significantly less likely to be selected, perhaps because consumers inferred compromised taste, or because applesauce is a fat-free food, so a “low-fat” claim is meaningless. Analyzing these consumer choices based on variations in product price showed that consumers were willing to pay more for locally grown applesauce than for applesauce labeled as organic, low-fat, or low in sugar.
Studies using different methods have come to similar conclusions—that value-labeled foods are generally preferred to those without such labels. Loureiro et al. (2001) used in-store intercept interviews to examine preferences for organic, eco-labeled, or regular apples in a random sample of shoppers (n = 285) in a grocery store produce section. Their findings showed that when offered at equal prices, consumers preferred organic apples to eco-labeled or regular apples.
The emerging fields of consumer neuroscience and neuromarketing bring new tools to understanding consumer reactions to products, packaging, and advertising (Kenning and Linzmajer, 2011; Morin, 2011). Using a variety of
methods like functional magnetic resonance imaging (fMRI), marketers and researchers can now examine how the brain processes product and advertising stimuli, and draw inferences based on the location and extent of heightened neural activity in the brain. Although there are no published studies to date using these methods to examine consumer reactions to FOP nutrition labels, several studies have examined other food package labels and claims, food package design, and food advertising.
Linder et al. (2010) showed participants (15 men, 15 women) images of 40 everyday foods that are routinely available in organic or non-organic forms. Participants viewed two versions of every image while inside the scanner, one with a widely used organic food symbol and one with an artificial symbol indicating conventional production (i.e., non-organic). When viewing images with the organic food label, neural activity increased in the ventral striatum, a part of the brain shown in previous research to be involved in anticipating pleasant taste rewards.
Stoll et al. (2008) tested reactions to attractive and unattractive packaging on actual food products widely available in Germany. In a preliminary study, 131 packages were rated on attractiveness and 30 were selected for use in an fMRI experiment: the 10 most attractive, the 10 least attractive, and 10 that were neutral (neither highly attractive nor unattractive). Attractive package designs triggered more activity in areas of the brain associated with attention and processing visual stimuli, while exposure to unattractive package designs triggered increased activity in areas of the brain associated with processing aversive stimuli.
In other studies, exposure to aesthetic (compared to standardized) beverage container designs increased activity in areas of the brain that are also activated by smiling faces (Reimann et al., 2010). Providing consumers with product information like claims that a food has “rich and delicious taste” or that a bottle of wine is very expensive has been associated with increased activity in an area of the brain associated with experiencing pleasantness when consumers received this information (vs. not receiving it) prior to tasting a product (Grabenhorst et al., 2008; Plassman et al., 2008).
Although these studies provide no direct evidence about how consumers might process FOP food labels, they reinforce findings from traditional marketing studies that indicate certain messages, designs, and labels on food products and packages can influence consumers’ reactions to and experiences with a product.
Although the findings described above focus on overall main effects of package label information, it is clear across many studies that these effects can vary among different sub-groups of consumers and across food categories. For example, in the Robinson et al. (2007) study of consumer preferences and “McDonald’s” branding on food packaging, the effects of branding were greatest among children with a television in their home and those who ate at a McDonald’s restaurant more frequently. In James et al. (2009), a choice study of applesauce, consumers with more knowledge about agriculture were less willing to pay more for organically and locally grown applesauce. In Loureiro et al. (2001), the preference for organic apples was strongest among consumers with children and those with greater concerns about food safety and the environment. And while the majority of children in Roberto et al. (2010) chose a snack that had a cartoon on the package, this effect was weaker for carrots than gummy fruit snacks or graham crackers.
These subgroup effects are highly consistent with well-established theoretical and empirical literature on information processing and persuasion. Previous experience (e.g., eating at branded fast-food restaurants), familiarity (e.g., seeing television advertisements for branded restaurants, knowing cartoon characters), issue involvement (e.g., concern about food safety and the environment), and personal relevance (e.g., having children that might be affected) all influence individuals’ attention, receptivity, and reactions to information in predicable ways (Petty and Cacioppo, 1979; Petty et al., 1981; Wu and Shaffer, 1987; Johnson and Eagly, 1989; Garcia-Marques and Mackie, 2001). Applied to FOP food labeling, care should be taken to design an approach that maximizes the impact of nutrition information for the greatest number of people, especially population sub-groups that historically have not used this information.
In summary, many elements of food packaging, including nutrition-related claims, branding, promotions, and other product information, have been shown to influence consumers’ product attitudes, preferences, and choices, at least in controlled and experimental settings.
Chapter 2 described the context in which consumers today would likely encounter FOP nutrition labels. In short, consumers are in a hurry, spending less time shopping for food and making very quick decisions at the point of purchase about individual products. These decisions are made in the face of a wide array of products, each of which comes in a unique package that may be decorated with some combination of branding, images, promotions, and claims about the product, how it is made, and its healthfulness. As described above, many of these package design features and product claims have been shown to influence consumer attitudes, preferences, and choices, at least in controlled settings and for some groups of consumers. These findings beg the question: What would make an FOP nutrition label stand out enough to have an impact in this environment?
All visual design relies on the idea of contrast (Dondis, 1974). To a large extent, manipulations in contrast between an object and background or among objects in a field determine what people pay attention to and how they understand its meaning. Contrast can be achieved by variations in color, size, shape, position, and other design features. For example, elements that are bigger, bolder, have more color contrast with the space around them, or are shaped differently generally will be noticed before smaller, lighter, commonly shaped, or subtle elements (Schiffman and Kanuk, 1983). Designers purposefully create, select, and arrange elements to be more or less prominent, calling attention to those they deem most important. This is true of food package design, too, and therefore relevant for FOP nutrition labeling. Both aim to capture consumer attention amidst many competing stimuli in a busy retail environment.
Theories and explanations of visual attention reinforce this design perspective, proposing that people attend to different features of a complex scene serially, starting with the most salient features (Treisman and Gelade, 1980; Koch and Ullman, 1985; Itti et al., 1998). In consumer studies, several researchers have tested this phenomenon empirically by examining consumer reactions to different stimuli in a cluttered information environment. Although none of these studies has directly examined attention to FOP nutrition labels on food packages, some pose information processing tasks that are roughly analogous to finding information on a busy food package.
Pieters et al. (2007) studied consumer attention to multi-component feature advertising for grocery stores. A newspaper advertisement showing a set of 10 to 20 “featured” products (e.g., sale items) on a single page is an example of this type of advertisement, and is considered by the researchers to be a “cluttered” environment. There are two key attributes of this type of advertisement. “Set size” refers to the number of different “components” (e.g., products) that make up the advertisement. “Set structure” refers to similarities or dissimilarities in the design or arrangement of the different components. In general, a larger set size and heterogeneous structure add to competitive clutter, making it harder for any individual component of the advertisement to stand out and attract attention (Rosenholtz et al., 2005). Thus the salience of any one advertisement component is likely determined by not only its own attributes, but also its contrast with the other components around it.
The study tested this proposition by analyzing eye-tracking data from consumer responses to 1,100 such advertisements. Eye tracking captures consumers’ visual attention to advertisements—where they looked, in what order, and for how long. This study focused on consumer attention to brand, text, images, price, and promotion information. Findings showed that consumer attention was greatest for components of the advertisements that were distinctive in some way from other components in the set (Pieters et al., 2007). The distinctiveness attribute with the greatest effect on attention was size—the larger a component of the advertisement, the more attention consumers paid to it. Other, similarly designed, eye-tracking analyses have compared consumer attention to pictures, brand, and text in print advertisements, finding that, among them, pictures are superior at capturing attention, regardless of size (Pieters and Wedel, 2004).
Lohse (1997) studied consumer responses to advertising in a different type of cluttered environment, Yellow Pages listings. Study participants (n = 32) were given a task of choosing a certain type of business in the Yellow Pages. Eye-tracking equipment was used to assess which listings and advertisements attracted the most attention. Color advertisements were noticed sooner than those without color and viewed longer than those without color, and overall more color ads were noticed than those without color (Lohse, 1997). Because most listings and advertisements use only black ink, the use of color enhances contrast with surroundings on the page. Size also captured attention. Consumers noticed nearly all (93 percent) of the quarter-page advertisements, but only 26 percent of the plain (i.e., text only) listings. Among plain listings, those using bold text were more likely to be viewed than those using normal text. Findings also showed that consumers spent 54 percent more time viewing businesses that they ended up choosing, therefore establishing a link between attention and choices.
Applied to food packages, these findings suggest that through visual design, some types of package information—branding, images, product claims, and even FOP nutrition labeling—can be made more prominent than others. It is possible, as Woolverton and Dimitri (2010) propose, that as the amount of package information increases, some consumers will be overwhelmed and unable (or unwilling) to process it all (Woolverton and Dimitri, 2010). Instead they will rely on simple cues, like branding or label claims, to make judgments about and comparisons among products.
Cue Utilization Theory and Signaling Theory suggest that under certain circumstances, consumers rely on extrinsic cues or signals as surrogate indicators of product quality (Richardson et al., 1994). The theories explain how consumers use product information to distinguish between better and lesser quality products when they have no direct experience with the products. For example, sellers of a high-quality product might use price, brand, or a warrantee to “signal” the higher quality of their product to consumers (Boulding and Kirmani, 1993; Nancarrow et al., 1998; Brucks et al., 2000). Food package claims and FOP labels might act as signals of quality or healthfulness for consumers. Signaling studies indicate that consumers are most likely to rely on signals for purchase decisions involving new or unfamiliar products (Richardson et al., 1994) when they are time stressed and need to make fast judgments about a product (Pieters and Warlop, 1999) and when their ability or motivation to process more complex information is limited (Jae and DelVecchio, 2004).
In a randomized experiment, Jae and DelVecchio (2004; Study 2) examined the effects of packaging cues on household consumer products among high- and low-literacy adults. All participants (n = 80) viewed a pair of identically priced paper towel products that varied in quality. By random assignment, packaging for the paper towels used either a plain or interesting design, and described product quality using either an informational approach (a bulleted list of product characteristics) or a simple symbol (a star-rating system). In every pair, the paper towel in plain packaging was of higher quality (i.e., the better choice, given equivalence in price). When the pair of products both described quality using a bulleted list, high-literacy adults chose the better paper towel in plain packaging, while low-literacy adults chose the inferior product in nice packaging. However, when the simpler star-rating system was used, there were no differences between high- and low-literacy adults choosing the better paper towel. These findings indicate that using simple symbols to summarize complex information about product quality may be especially valuable to low-literacy populations.
The strength of simple visual communication also has been demonstrated in consumer studies of reactions to certain types of food labels. Kapsak et al. (2008) conducted a web-based study of 5,642 U.S. adults to evaluate a possible FDA label system that graded the strength of scientific evidence behind health claims made on food packages. Participants viewed packages of orange juice, pasta sauce, or breakfast cereal containing health claims that were well known (orange juice—calcium), moderately well known (pasta sauce—lycopene) or fictitious (cereal—trilinium). Each package also contained one of four versions of a label that rated the strength of the evidence behind the health claim: report card graphic, report card text, embedded claim text, or point-counterpoint claim text. Finally, the strength of evidence was varied within each label format for each product. Participants viewed two-dimensional color images of each food package and could toggle between front, back, and side views of the product.
The simplest format—a report card graphic using letter grades (A-D) to reflect strength of evidence—performed best. It was the only format tested in which consumers did not have difficulty distinguishing between the four levels of evidence. Although FDA never implemented this labeling system, the investigators summarized their findings as suggesting “the strength of visual communication over text on food labels” and the value of “simple, direct, and positive messaging to consumers about the health benefits of foods” (p. 255).
FOP food labeling, especially using a simple symbol, might serve as a cue or signal for consumers. Although there are some label claims that could be made by any food product regardless of its nutritional quality (e.g., “Moms love it”), fact-based claims about a standard set of nutrients could be made only by those that meet some predetermined nutritional standard. Thus consumers might view an objective, uniform FOP nutrition label as a kind of signal, helping distinguish between products of greater and lesser nutritional quality.
Another labeling system, Energy Star®, already uses this approach to help consumers judge the energy efficiency and energy costs of durable goods such as consumer electronics and household appliances (Box 6-1). Energy Star® is a U.S. government–based program jointly led by the Environmental Protection Agency (EPA) and Department of Energy (DoE). Products that meet energy efficiency standards set by EPA and DoE can carry the Energy Star® label—a simple blue square bearing the program name—and manufacturers and retailers can use Energy Star® branding to advertise and market approved products. In a 2003 review of eco-labeling programs for energy efficiency, Banerjee and Solomon (2003) singled out Energy Star® as particularly successful, and concluded that one reason for its impact was the clarity and simplicity of its label. They asserted that across all programs, simpler labels like the Energy Star® logo were more useful to consumers. Citing repeated consumer complaints about other types of labels that focused on information disclosure, they observed that “the proportion of informed consumers who are willing and able to use technical information effectively is low” (p. 120).
There might also be unintended effects of nutrition cues or signals on food packages. One of the most consistent findings in studies of consumer reactions to package claims is the tendency of consumers to over-generalize the healthfulness of a product based on claims about a specific nutrient (e.g., Andrews et al., 1998; Kozup et al., 2003; Gorton et al., 2010; Labiner-Wolfe, 2010). A study by Horgen and Brownell (2002) suggested that consumers might interpret a favorable rating on an FOP nutrition label as a signal that the food does not taste good. It is also possible that different labels on a product package could signal conflicting information to consumers, in which case effectiveness of both may be diminished. For example, the FOP nutrition label for a particular food might indicate it is a less healthful choice while the manufacturer’s nutrient content claim on the same package announces that the food is “a good source of vitamin A.” Because nutrition-related claims are fairly common—even on products that exceed FDA-recommended levels of fat and sodium (Harris et al., 2009; Colby et al., 2010)—the effects of any new FOP-package labeling system should be evaluated in this specific context.
The location of an FOP nutrition label may also influence the likelihood that consumers attend to and use it. Visual search studies suggest that when viewing certain types of stimuli, humans rely on familiar “scan paths” or “saliency maps” that are encoded in memory from similar visual search situations in the past (Koch and Ullman, 1985; Itti et al., 1998; Rybak et al., 2005). These paths or maps reflect established patterns of knowing “where” to look to find “what” information in a particular context. As an example, when regular shoppers view items on a grocery store shelf, they know to look at shelf tags to find product prices. If FOP nutrition symbols were located in the same place on every food package (e.g., upper right-hand corner), then it would be expected that some consumers might develop a scan path in which they always looked in this place for nutrition information. When they encountered a new package, cognitive processes would select and follow this established path for processing package information.
These scan paths can be influenced by training (Itti, 2005). So-called “pre-attentive” prompts can help individuals locate information in a busy or complex landscape (Wolfe, 2005). At the simplest level, such prompts might tell consumers where to look to find a FOP nutrition label (e.g., upper right-hand corner). More specific prompts that also indicate what to look for should have an even greater impact on attention (Wolfe, 1994). In 2005, Wolfe proposed a typology of probable, possible, and unlikely sources of pre-attentive guidance. The list of probable
Created in 1992 by the U.S. Environmental Protection Agency (EPA), the Energy Star® program aims to reduce energy use and greenhouse gas emission by helping consumers and businesses identify energy efficient products. Products that meet energy efficiency standards set by EPA and the Department of Energy (DoE) can carry the Energy Star® label, and manufacturers and retailers can use Energy Star® branding to advertise and market approved products. Qualified products include a wide range of appliances, consumer electronics, lighting fixtures, heating and cooling equipment, office equipment, and items from more than 50 other product categories.
For consumers, the Energy Star® label signals products that deliver the same or better performance as comparable models while using less energy and saving money. Consumer awareness of Energy Star is high, and the program appears to influence purchase behavior. The Energy Star® label is recognized by 80 percent of the American public. In 2010, Americans bought 200 million Energy Star® –qualified products from more than 60 different product categories. One-third of U.S. households have purchased an Energy Star® labeled appliance, and of these purchases, 75 percent of consumers report that the Energy Star® label was an important factor in their decision. Both consumers and the environment benefit from these purchases. EPA reports that in 2010, Energy Star® helped save households and businesses $18 billion on utility bills and prevented 170 million metric tons of greenhouse gas emissions.
In a 2003 review of eco-labeling programs for energy efficiency, Banerjee and Solomon (2003) singled out Energy Star® as particularly successful, and concluded that one reason for its impact was the clarity and simplicity of its label. They asserted that across all programs, simpler labels such as the Energy Star® logo were more useful to consumers. Citing repeated consumer complaints about other types of labels that focused on information disclosure, they observed that “the proportion of informed consumers who are willing and able to use technical information effectively is low” (p. 120).
At least five other factors have contributed to the success of the Energy Star® program, and each has relevance for designing and implementing a FOP nutrition labeling program for foods:
• Partnerships with key stakeholders, including thousands of public- and private-sector organizations that manufacture, sell, or use qualified products.
• Widespread market penetration for Energy Star Energy Star®, with more than 40,000 individual products now carrying the program label.
• A dynamic and evolving program that in less than 20 years has grown from a few personal electronicsproducts, to near ubiquity among household electronics and appliances, to buildings and homes and the materials used to make them. It also constantly reviews its energy efficiency guidelines to make sure qualifying standards are sufficiently demanding and reflect advances in technology.
• Ongoing and multi-faceted promotions are used to assure that Energy Star® remains prominent and attractive to consumers, manufacturers, and retailers. These include awareness campaigns, tax incentives, and rebates for consumers, an online presence, and public recognition of partner organizations and highly compliant manufacturers. Finally, funding is dedicated to support these activities. In FY 2010, EPA appropriated $55.5 million for Energy Star®.
sources included color, size, shape, and number. Applied to FOP nutrition labeling, telling consumers to look for “three yellow stars in the upper right hand corner” could increase the likelihood that they will find and attend to this information.
A recent and comprehensive study of FOP nutrition rating systems lends strong empirical support to these propositions. Bialkova and van Trijp (2010) assessed consumer response time and accuracy and ability to distinguish between single and multiple nutrition labels on pictures of actual food packages currently on the market. Each participant (n = 24) viewed 193 packages on a computer screen. Packages varied systematically based on the type of nutrition label (“Choices” logo, monochrome Guideline Daily Amount [GDA], multi-colored GDA), its size and location, and whether the package included both a “Choices” and GDA label, or only one. Participants were asked to indicate as fast as possible whether or not any nutrition label was present (Task 1) and whether one or two labels were present (Task 2). Responses were timed and checked for accuracy.
Findings showed that participants’ responses were significantly faster when the nutrition label appeared in the same location as the previous trial (i.e., consistency of location across multiple successive exposures). It follows that if nutrition labels were located in different positions on different food packages, then it would take consumers longer to find and use them. Reactions were fastest when the label was in the top right position.
Other findings from the study were equally applicable to the design and implementation of an FOP nutrition labeling system. For example, participants were able to identify the “Choices” label faster than the GDA label. In contrast to the data-laden GDA label, the “Choices” label is a simple check mark logo. This finding reinforces those of previous consumer studies showing simpler labels have advantages over more complex ones (e.g., Banerjee and Solomon, 2003; Jae and DelVecchio, 2004; Kapsak et al., 2008). Among the two GDA labels, reaction time was faster for the monochromatic vs. multi-color version, and for all labels, larger size led to faster response time. The investigators hypothesize that the physical features of a nutrition label—its size, color, shape, and location are key determinants of consumer attention to the label.
Many studies have examined effects of different types of food package information on consumer preferences, choices, and behavior. These studies demonstrate that such information can influence consumers, and likely affects some groups more than others, including those with less knowledge about or interest in nutrition. One limitation of this research is its low external validity. Many studies are conducted in controlled or online settings and use simulated packages and labels rather than actual products. Such studies afford researchers the opportunity to easily manipulate and test different package labeling features, but ignore the complexity of the shopping environment. This complexity exists at both a macro level (e.g., many similar products side by side in a store aisle) and at a micro level (e.g., many instances of branding, promotion, labeling, claims, and other information on a single package). In order to design an optimal FOP nutrition labeling system, it is essential to understand how consumers process information in a busy, cluttered environment.
To succeed, FOP nutrition labels would need to stand out and capture attention in this busy and competitive food package environment. Principles of visual design, theories of visual search and empirical evidence from well-designed studies suggest that a label would need to be distinctive and contrast with other information around it. Distinctiveness might be achieved through a label’s design features including its size, shape, color, and/or location. Moreover, if consumers can be conditioned to look in certain places for a certain type of label, the repetition in location and appearance could help them find nutrition labels faster.
Labels conveying information via a simple symbol may also be beneficial to consumers. Studies of food package labels and other consumer product labeling indicate that compared to other types of labels, simpler symbols may be easier for consumers to find, may be more useful to them, help them distinguish between levels on an ordinal scale, and may influence their product choices. Some of these advantages may be particularly beneficial to disadvantaged populations. In one study, a simple symbol improved decision-making about consumer products in low-literacy populations.
Still unclear is how FOP nutrition symbols might perform in the presence of other nutrition-related label claims, especially those highlighting a nutrient that is not addressed by the FOP system. Findings from several studies indicate this is likely to be a common occurrence, and theories suggest it could diminish or negate possible benefits of a nutrition label. Future research should explore this possibility.
This chapter examined effects of package information on consumer preferences and choices, and explored how consumers process package information in the face of multiple competing stimuli. Because literature that addressed these topics and was also specific to FOP nutrition labels was relatively sparse, the committee also considered literature from related domains. These included studies examining other consumer products (i.e., non-food), other information stimuli (e.g., advertising), and theories and findings from a range of disciplines including visual design, marketing, information search and retrieval, and attention and information processing.
Although no definitive, proven best FOP strategy was identified, in the committee’s judgment, the collective literature reviewed in this chapter strongly suggest a certain approach. Consumers are making point-of-purchase decisions about food products in very little time and in the face of a diverse and growing number of stimuli on food packages. The characteristics of an FOP nutrition labeling system that would cause it to stand out in this environment, capture consumers’ attention, and be accessible and useful to a diverse cross-section of American consumers are:
1. A simple symbol, signal, or cue that instantly conveys meaning without written information, percentages, or other nutrition data or statistics;
2. Placement of the symbol in the same location on all food packages;
3. A design that maximizes the symbol’s visual contrast with existing elements of packaging;
4. Assurance that the symbol is sufficiently prominent in size to compete effectively with other package elements and attract consumer attention; and
5. A complementary campaign that guides consumers to look in a specific location for the specific symbol.
Andrews, J. C., R. G. Netemeyer, and S. Burton. 1998. Consumer generalization of nutrient content claims in advertising. Journal of Marketing 62:62-75.
Aschemann-Witzel, J., and U. Hamm. 2010. Do consumers prefer foods with nutrition and health claims? Results of a purchase simulation. Journal of Marketing Communications 16:47-58.
Banerjee, A., and B. D. Solomon. 2003. Eco-labeling for energy efficiency and sustainability: A meta-evaluation of U.S. programs. Energy Policy 31:109-123.
Bialkova, S., and H. van Trijp. 2010. What determines consumer attention to nutrition labels? Food Quality and Preference 21:1042-1051.
Blitstein, J. L., and W. D. Evans. 2006. Use of Nutrition Facts panels among adults whom make household food purchasing decisions. Journal of Nutrition Education and Behavior 38:360-364.
Boulding, W., and A. Kirmani. 1993. A consumer-side experimental examination of signaling theory: Do consumers perceive warranties as signals of quality? Journal of Consumer Research in Engineering Design 20:111-123.
Brucks, M., V. A. Zeithaml, and G. Naylor. 2000. Price and brand name as indicators of quality dimensions for consumer durables. Journal of the Academy of Marketing Science 28:359-374.
Colby, S. E., L. Johnson, A. Scheett, and B. Hoverson. 2010. Nutrition marketing on food labels. Journal of Nutrition Education and Behavior 42:92-98.
Dondis, D. A. 1974. Primer of Visual Literacy. Cambridge, MA: MIT Press.
Drewnowski, A., H. Moskowitz, M. Reisner, and B. Krieger. 2010. Testing consumer perception of nutrient content claims using conjoint analysis. Public Health Nutrition 13:688-694.
Elliott, C. 2008. Assessing “fun foods:” Nutritional content and analysis of supermarket foods targeted at children. Obesity Reviews 9:368-377.
Garcia-Marques, T., and D. M. Mackie. 2001. The feeling of familiarity as a regulator of persuasive processing. Social Cognition & Emotion 19:9.
Gorton, D., C. N. Mhurchu, D. Bramley, and R. Dixon. 2010. Interpretation of two nutrition content claims: A New Zealand survey. Australian and New Zealand Journal of Public Health 34:57-62.
Grabenhorst, F., E. T. Rolls, and A. Bilderbeck. 2008. How cognition modulates affective responses to taste and flavor: Top-down influences on the orbitofrontal and pregenual cingulate cortices. Cerebral Cortex 18:1549-1559.
Guthrie, J. F., J. J. Fox, L. E. Cleveland, and S. Welsh. 1995. Who uses nutrition labeling and what effect does label use have on diet quality? Journal of Nutrition Education 27:163-172.
Harris, J., M. Schwartz, K. Brownell, V. Sarda, M. E. Weinberg, S. Speers, J. Thompson, A. Ustjanauskas, A. Cheyne, E. Bukofzer, L. Dorfman, and H. Byrnes-Enoch. 2009. Cereal Facts: Evaluating the Nutrition Quality and Marketing of Children’s Cereals. New Haven, CT: Rudd Center for Food Policy and Obesity.
Horgen, K. B., and K. D. Brownell. 2002. Comparison of price change and health message interventions in promoting healthy food choices. Health Psychology 21:505-512.
Itti, L. 2005. Models of bottom-up attention and saliency. In Neurobiology of Attention, edited by L. Itti, G. Rees, and J. K. Tsotsos. Burlington: Academic Press. Pp. 576-582.
Itti, L., C. Koch, and E. Niebur. 1998. A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 20:1254-1259.
Jae, H., and D. DelVecchio. 2004. Decision making by low-literacy consumers in the presence of point-of-purchase information. Journal of Consumer Affairs 38:342-353.
James, J., B. Rickard, and W. Rossman. 2009. Product differentiation and market segmentation in applesauce: Using a choice experiment to assess the value of organic, local, and nutrition attributes. Agricultural and Resource Economics Review 38:357-370.
Johnson, B., and A. Eagly. 1989. Effects of involvement on persuasion: A meta-analysis. Psychological Bulletin 106:290-314.
Kapsak, W. R., D. Schmidt, N. M. Childs, J. Meunier, and C. White. 2008. Consumer perceptions of graded, graphic and text label presentations for qualified health claims. Critical Reviews in Food Science and Nutrition 48:248-256.
Kenning, P., and M. Linzmajer. 2011. Consumer neuroscience: An overview of an emerging discipline with implications for consumer policy. Journal of Consumer Protection and Food Safety 6:111-125.
Koch, C., and S. Ullman. 1985. Shifts in selective visual attention: Towards the underlying neural circuitry. Human Neurobiology 4:219-227.
Kozup, J., E. Creyer, and S. Burton. 2003. Making healthful food choices: The influence of health claims and nutrition information on consumers’ evaluations of packaged food products and restaurant menu items. Journal of Marketing 67:19-34.
Labiner-Wolfe, J., C. T. J. Lin, and L. Verrill. 2010. Effect of low-carbohydrate claims on consumer perceptions about food products’ healthfulness and helpfulness for weight management. Journal of Nutrition Education and Behavior 42:315-320.
Linder, N. S., G. Uhl, K. Fliessbach, P. Trautner, C. E. Elger, and B. Weber. 2010. Organic labeling influences food valuation and choice. Neuroimage 53:215-220.
Lohse, G. L. 1997. Consumer eye movement patterns on yellow pages advertising. Journal of Advertising 26:61-73.
Loureiro, M. L., J. J. McCluskey, and R. C. Mittelhammer. 2001. Assessing consumer preferences for organic, eco-labeled, and regular apples. Journal of Agricultural and Resource Economics 26:404-416.
Morin, C. 2011. Neuromarketing: The new science of consumer behavior. Society 48:131-135.
Morton, J., and J. F. Guthrie. 1997. Diet-related knowledge, attitudes, and practices of low-income individuals with children in the household. Family Economic Nutrition Reviews 10:2-15.
Nancarrow, C., L. T. Wright, and I. Brace. 1998. Gaining competitive advantage from packaging and labelling in marketing communications. British Food Journal 100:110-118.
Petty, R. E., and J. T. Cacioppo. 1979. Issue involvement can increase or decrease persuasion by enhancing message-relevant cognitive responses. Journal of Personality and Social Psychology 37:1915-1926.
Petty, R. E., J. T. Cacioppo, and R. Goldman. 1981. Personal involvement as a determinant of argument-based persuasion. Journal of Personality and Social Psychology 41:847-855.
Pieters, R., and L. Warlop. 1999. Visual attention during brand choice: The impact of time pressure and task motivation. International Journal of Research Marketing 16:1-17.
Pieters, R., and M. Wedel. 2004. Attention capture and transfer in advertising: Brand, pictorial, and text-size effects. Journal of Marketing 68:36-50.
Pieters, R., M. Wedel, and J. Zhang. 2007. Optimal feature advertising design under competitive clutter. Management Science 53:1815-1828.
Plassmann, H., J. O’Doherty, B. Shiv, and A. Rangel. 2008. Marketing actions can modulate neural representations of experienced pleasantness. Proceedings of the National Academy of Sciences of the United States of America 105:1050-1054.
Reimann, M., J. Zaichkowsky, C. Niehaus, T. Bender, and B. Weber. 2010. Aesthetic package design: A behavioral, neural, and psychological investigation. Journal of Consumer Psychology 20:431-441.
Richardson, P. S., A. S. Dick, and A. K. Jain. 1994. Extrinsic and intrinsic cue effects on perceptions of store brand quality. Journal of Marketing 58:28-36.
Roberto, C. A., J. Baik, J. L. Harris, and K. D. Brownell. 2010. Influence of licensed characters on children’s taste and snack preferences. Pediatrics 126:88-93.
Robinson, T. N., D. L. G. Borzekowski, D. M. Matheson, and H. C. Kraemer. 2007. Effects of fast food branding on young children’s taste preferences. Archives of Pediatric and Adolescent Medicine 161:792-797.
Rosenholtz, R., Y. Li, J. Mansfield, and Z. Jin. 2005. Feature congestion: A measure of display clutter. Paper read at SIGCHI 2005 Conference on Human factors in Computing Systems, Portland, OR.
Rybak, I. A., V. I. Gusakova, A. V. Golovan, L. N. Podladchikova, and N. A. Shevtova. 2005. Attention-guided recognition based on “what” and “where” representations: A behavioral model. In Neurobiology of Attention, edited by L. Itti, G. Rees, and J. K. Tsotsos. Burlington: Academic Press. Pp. 663-670.
Satia, J. A., J. A. Galanko, and M. L. Neuhouser. 2005. Food nutrition label use is associated with demographic, behavioral and psychosocial factors and dietary intake among African Americans in North Carolina. Journal of the American Dietetics Association 105:392-402.
Schiffman, L. G., and L. Kanuk. 1983. Consumer Behavior. 2nd ed. Englewood Cliffs, NJ: Prentice-Hall.
Schofield, H., and S. Mullainathan. 2008. The psychology of nutrition messages. Advances in Health Economics and Health Services Research 19:145-172.
Stoll, M., S. Baecke, and P. Kenning. 2008. What they see is what they get? An fMRI-study on neural correlates of attractive packaging. Journal of Consumer Behaviour 7:342-359.
Todd, J. E., and J. N. Variyam. 2008. The Decline in Consumer Use of Food Nutrition Labels, 1995-2006, Economic Research Report No. 63, Economic Research Service, U.S. Dept. of Agriculture.
Treisman, A. M., and G. A. Gelade. 1980. A feature-integration theory of attention. Cognitive Psychology 12:97-136.
Verbeke, W., J. Scholderer, and L. Lahteenmaki. 2009. Consumer appeal of nutrition and health claims in three existing product concepts. Appetite 52:684-692.
Wolfe, J. M. 1994. Guided search 2.0: A revised model of visual search. Psychonomic Bulletin & Review 1:202-238.
Wolfe, J. M. 2005. Invited paper: How might the rules that govern visual search constrain the design of visual displays? Society for Information Display, International Symposium Digest of Technical Papers 2:1395-1397.
Woolverton, A., and C. Dimitri. 2010. Green marketing: Are environmental and social objectives compatible with profit maximization. Renewable Agriculture and Food Systems 25:90-98.
Wu, C., and D. R. Shaffer. 1987. Susceptibility to persuasive appeals as a function of source credibility and prior experience with the attitude object. Journal of Personality and Social Psychology 52:677-688.