Food for Thought: How Will the Nutrition Labeling of Quick ServiceRestaurant Menu Items Influence Consumers’ Product Evaluations,
Purchase Intentions, and Choices?
Scot Burton ∗, Elizabeth Howlett, Andrea Heintz TangariDepartment of Marketing and Logistics, Sam M. Walton College of Business, 302 WCOB, University of Arkansas, Fayetteville, AR 72701, United States
bstract
Within the context of quick service restaurant meals, three studies (a consumer diary study, web-based experiment, and longitudinal experiment)xamine how accurately consumers estimate calorie, fat, and sodium content and explore how objective nutrition information may influenceroduct evaluations, perceptions, and purchase intentions. The results indicate that many consumers have little understanding of the calorie, fat,nd sodium levels of many typical quick service meals, and this is especially true for less healthful meals. Consistent with rationale drawn from
he expectancy-disconfirmation paradigm, results demonstrate that menu-based nutrition information provision negatively influences consumers’esponses when that information is less favorable than expected. Findings suggest that the relationship between actual and expected nutrition levelsrives responses, rather than the disclosure of information per se. Since these relationships can vary both within and between restaurants, resultsuggest that the effects of mandated nutrition information disclosure may not be uniform across the industry.
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2009 New York University. Published by Elsevier Inc. All rights res
eywords: Menu labeling; Calorie expectations; Calorie disclosures; Restauran
Many quick service and table service restaurant retailers nowace potentially significant market changes. Legislation thatould mandate the provision of calorie and nutrient informationn restaurant menus and menu boards has been proposed atederal, state, and local levels. The impetus for this proposedegislation is the rising prevalence of overweight and obesity,hich is associated with a number of chronic diseases includingeart disease, stroke, and type 2 diabetes (Centers for Diseaseontrol (CDC) 2008). With over $500 billion spent annuallyn food from quick and table service restaurants (accountingor almost one-half of American’s food expenditures), changesithin this retailing environment potentially may have sig-ificant implications for many consumers, specific restauranthains, and the retail restaurant industry in general (Nationalestaurant Association 2008; United States Department of
griculture 2008).The positive relationship between rising obesity rates and
ncreases in consumer spending at restaurants has not gone unno-
iced by a number of public policy makers and public interestroups. This increase in away-from-home food consumption andhe rise in obesity rates have raised questions regarding bothhe healthfulness of food prepared by restaurant retailers andonsumers’ awareness of the influence away-from-home foodonsumption may have on the outcome of their weight mainte-ance and weight-loss attempts. Quick service restaurants haveften been specifically targeted for their potential role in con-ributing to the national obesity problem by selling foods highn calories and negative nutrients in overly large portions.
Legislation mandating the disclosure of calorie and nutrientnformation on menus and menu boards has been signed into lawn California and introduced in over 20 other states and munici-alities. The Menu Education and Labeling Act and the Labelingducation and Nutrition Act have been under consideration by
he United States Congress. Yum Brands, the parent companyf KFC, Taco Bell, and Pizza Hut, announced in October, 2008,hat it will (voluntarily) present product calorie information on
enu boards in its company-owned U.S. restaurants by January,011, the same date on which the California legislation goes into
ull effect (Horovitz 2008).
These initiatives are likely to affect many of the product offer-ngs of firms within this $500 billion dollar retail industry. Theoal of our research is to provide insight regarding how the pro-
ision of calorie and nutrient information on restaurant menusnd menu boards may influence consumers’ product evaluations,erceptions of diet-related disease risks, purchase intentions, andtem choices. An improved understanding of how consumers
ay respond to the provision of calorie and nutrient informa-ion in the context of away-from-home food consumption willetter inform retailers’ decision making processes as they assesshis dynamic business environment. Specifically, we address theollowing research questions:
. How accurately do consumers estimate the calorie, fat, andsodium content of their actual fast food meal purchases?
. How do the disclosure of nutrition information and initialcalorie expectations interact to influence meal evaluations,purchase intentions, and choice? Are these effects similaracross different quick service retail restaurants?
Study 1
ackground and predictions
In most restaurant environments, product attributes such asalories, protein, fat, and sodium, can generally be viewed as cre-ence attributes since most consumers cannot accurately assessr verify their levels even after product consumption (Caswellnd Mojduszka 1996; Darby and Karni 1973). For example, its impossible to determine the fat and calorie content of a largetarbucks muffin simply through purchase and consumption.owever, this has not been the case with consumer packaged
oods since passage of the National Labeling and Education ActNLEA); nutrient and calorie content, and percent daily valuesre available on a per serving basis in the Nutrition Facts panel.hus, inherently credence attributes have been transformed intoearch attributes that consumers can easily assess prior to con-umption with minimal search costs.
While calorie and nutrient attributes may be consideredearch attributes for most packaged foods (Caswell and
ojduszka 1996), foods purchased from restaurants are exemptrom NLEA disclosure requirements. Cues obtained throughroduct experience (i.e., product taste) and prior market knowl-dge enable consumers to make relative comparisons of theutritional content of foods prepared at quick service restau-ants. For example, we suspect that although most consumersan correctly infer that a Burger King Whopper has more calo-ies and fat than a 6 in. Subway turkey sub, they may have littlenowledge of absolute calorie differences.
Clearly, relative to packaged food products, consumer searchosts associated with nutrition-related attribute informationre higher for foods prepared outside the home. For manyonsumers, these search costs probably exceed the perceivedenefits of that information. The absolute, quantitative values ofalories and nutrients such as fat and sodium remain credenceroperties and thus consumer knowledge of these attributes is
ikely to be very low. This is consistent with findings that demon-trate that for some foods purchased at specific quick serviceestaurants (e.g., Subway and McDonald’s) and for some foodse.g., Fettuccine Alfredo) typically available at table service
tiiw
ling 85 (3, 2009) 258–273 259
estaurants, consumers’ absolute and percentage underestima-ion of calorie levels increase as meal calorie levels increase (e.g.,urton et al. 2006; Wansink and Chandon 2006). Properties ofsychophysics may account for this effect; studies show thathere is less sensitivity to increases in magnitude as the absoluteize of a stimulus increases (Chandon and Wansink 2007b).
Study 1 extends prior research both by considering a greaterariety of menu options from a wider set of quick serviceestaurants and by employing a different type of methodology.urthermore, nutrients with significant health-related implica-
ions, as well as calories, are considered. Although “calories”s often the most salient attribute during the choice process of
any consumers because of its weight-related implications, fatnd sodium content are also often highly salient because of theirssociation with diseases and health conditions such as coronaryeart disease, cancer, and hypertension. Thus, an initial objec-ive of Study 1 is to partially replicate prior findings related tostimated calorie consumption and extend this prior researcho additional nutrients, retailers, and consumer segments (cf.urton et al. 2006; Chandon and Wansink 2007a; Wansink andhandon 2006). Specifically, we examine how accurately con-
umers estimate the calorie, sodium, and fat content of theirestaurant food purchases. In addition, how the estimates and theccuracy of these estimates differ across quick service restau-ants and gender is considered.
The primary objective of Study 1 involves the interactionetween meal calorie level and exposure to objective nutri-ion information. How the provision of objective calorie andutrient information may influence consumers’ evaluations andurchase behaviors is important for both public policy mak-rs and those in the restaurant industry to understand. Drawingrom expectancy disconfirmation theory (van Raaij 1991), weuggest that consumers form initial expectations about specificutrition attributes which vary with respect to objective levels.ccording to expectancy disconfirmation theory, attribute dis-
atisfaction occurs when objective attribute information does noteet expectations. When this occurs, attitudes toward the prod-
ct should be more negative and repurchase intentions shoulde lower (Grunert 2005; van Raaij 1991). However, more favor-ble attitudes and higher repurchase intentions result if actualttribute levels meet or exceed expectations (e.g., calorie lev-ls are below or consistent with expected levels). If calorie andutrient content of restaurant foods are credence attributes, thenonfirmation/disconfirmation processes cannot occur which, inurn, suggests that consumers’ product evaluations should not beffected. However, consumers will have an objective basis forhe confirmation or disconfirmation of their expectations whenhese values are transformed into search attributes through therovision of highly accessible nutrition information.
Thus, when consumers choose lower calorie (and health-er) meals from fast food restaurants, exposure to the objectiveutrition information for these meals is more likely to confirmfavorable) initial expectations. Using a mock menu for a ficti-
ious table-service restaurant, Burton et al. (2006) reported annteraction between nutrition information disclosure and menutem; menu items had either relatively low (e.g., a turkey sand-ich) or high calorie (e.g., a large hamburger with fries) levels
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60 S. Burton et al. / Journal of
nd nutrition information was either presented or not presented.nformation disclosure had a stronger negative impact on theigher calorie meals which suggests that calorie level moderateshe effects of nutrition information provision. In contrast to this
ock choice situation, we focus on previously purchased fastood meals. In this context of actual product consumption, repur-hase intentions are likely to be influenced by both the provisionf nutrition information and by a variety of other marketingnd nonmarketing variables (e.g., taste, price, food preference)s well. When consumers purchase higher calorie meals, calo-ie expectations are more likely to be disconfirmed. Therefore,valuations and meal repurchase intentions should decrease.owever, meal evaluations and repurchase intentions should
ncrease or remain stable after exposure to the nutrition informa-ion when lower calorie meals are purchased (i.e., when caloriexpectations are more likely to be confirmed). We predict:
1. For meals purchased from quick service restaurants, thebjective calorie level of the meals will moderate the effectf exposure to nutrition information on perceived (a) calorieevel attractiveness, (b) weight gain likelihood, (c) heart diseaseikelihood, (d) meal healthfulness, and (e) repurchase intentions.
tudy 1 method
In Study 1, diary data of fast food purchases were mergedith survey data of participants’ product perceptions and
epurchase intentions. There were four primary stages of dataollection. In the initial stage, participants kept a seven-dayiary of their visits to fast food outlets; the specific foodnd drinks consumed (and condiments used), the restaurantshere the purchases occurred, meal prices, and ratings of meal
atisfaction were recorded. During the data collection period,articipants were reminded to record their fast food visits.here was no mention of meal-related calorie or nutrient levelsuring this initial data collection stage.
After the seven-day diaries were finished, participants esti-ated the calorie, fat, and sodium levels for each restaurant meal
ecorded in their diary.1 During this second stage of the data col-ection process, for each specific meal purchased, ratings of mealealthfulness, calorie level attractiveness, likelihood of gainingeight and developing heart disease if the meal was included asregular component of their weekly diet, and likelihood of meal
epurchase were obtained. In the third stage, participants visitedestaurant websites to obtain the objective calorie and nutrientevels of each meal. A few days after obtaining this objectivenformation, participants reevaluated their meal purchases onhe five measures noted above, without access to any of their
rior responses. Thus, these product evaluation and repurchasentention measures were assessed at two points in time, once sev-ral days before and once several days after obtaining objectiveutrition information.
1 Respondents were provided “daily value levels” consistent with those foundn the bottom portion of the Nutrition Facts panel. In pilot tests, we found thathen daily values are not provided for nutrients such as sodium, most consumers
ack the knowledge to make reasonable estimates.
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ling 85 (3, 2009) 258–273
A total of 155 junior and senior undergraduate students par-icipated in the study; 96 percent of the participants reportedating at a fast food restaurant during the seven-day period. Morehan 500 total fast food experiences were recorded; the averageumber of fast food meals consumed was 3.8 (SD = 2.2). Forach fast food meal purchased, single item measures employ-ng a nine-point response scale were used to assess the calorieevel perceptions, meal healthfulness, and likelihood of mealepurchase. As noted above, these measures were assessed bothefore and after objective nutrition information was acquired,eparated by a one-week period. Endpoints for the calorie andeal healthfulness evaluations were “very unfavorable” (1) to
very favorable” (9). For the likelihood of gaining weight andeveloping heart disease measures, subjects were asked if theyte the meal regularly as part of their diet, did they think thathe product would (decrease/increase) the likelihood of gainingeight or developing heart disease (Kozup, Creyer, and Burton003) with endpoints of “would decrease the likelihood” (1) towould increase the likelihood” (9).
tudy 1 results
nitial findings concerning calorie and nutrient estimatesThe first column of Table 1 shows (1) consumers’ esti-
ated calorie and nutrient levels, (2) actual calorie and nutrientevels obtained from corporate websites, and (3) accuracy mea-ures, that is, differences between the estimated and actualevels, across all fast food meals. Consistent with prior researchddressing calorie estimates, meal calories (−243), fat (−9.6 g),nd sodium (−1,011 mg) levels were all underestimated. Aeries of t tests assessed whether the accuracy measures wereignificantly different from zero; t values ranged from −21.5 to8.9 (df = 503; p < .001 for all), indicating significance across alleals. Consistent with prior findings showing that as calorie lev-
ls increase, underestimation increases (Wansink and Chandon006), the Pearson correlations between objective calorie andutrient levels (obtained from the websites) and the accuracyeasures are all negative and significant (r’s range between −.58
or calories to −.77 for sodium; p < .001 for calories, fat, andodium).2
Table 1 also highlights differences between retail chains.n a series of MANOVAs, consumers’ estimates, actual calo-ie and nutrient levels, and accuracy measures for calories, fat,nd sodium served as the dependent measures while restauranthain served as the independent variable. Generally, not onlyo estimated calorie and nutrient levels of the purchased foodtems differ across retailers, actual levels and accuracy measuresiffer as well. Also, given that the F values are greater for actual
utrition levels than for the estimated values, these between-etailer differences appear larger than participants realize. Inther words, consumers do not seem to fully realize the degree
2 Further examination of the diary data indicate that as meals became largere.g., more than 1000 calories), underestimation increases. In addition, wexamined the relationship between actual and estimated calories and found a sig-ificant nonlinear component that slightly improved fit. However, the nonlinearomponent in similar analyses for fat and sodium did not reach significance.
S.Burton
etal./JournalofRetailing
85(3,2009)
258–273261
Table 1Study 1: Fast food meal estimates, actual meal values, and accuracy measures for calories, fat, and sodium.
Total (n = 504) Burger King McDonald’s Wendy’s Sonic Arby’s Taco Bell Chick-fil-A Subway F valuesa,b
*p < .10; ***p < .01.a Different numerical superscripts in the table indicate a significant difference (p < .05) between means based on SNK contrasts. For example, for Burger King (superscript of 4), the actual meal calories differ
from Sonic, Taco Bell, Chic-fil-A, and Subway (none with superscripts of 4), but it is not significantly different from Wendy’s, McDonald’s, and Arby’s (all with superscripts of 4). Sample sizes range from 29 to 76meals across the eight restaurants.
b Degrees of freedom for all univariate F tests range between (7,345) and (7,356).c The accuracy measure score represents the estimated number of calories for the meal minus the actual calorie level calculated from the restaurant’s website. Negative numbers indicate that the number of calories
in the meal is underestimated by the consumer; positive numbers indicate the number of calories is overestimated.d Numbers shown for fat are in grams; sodium levels are in milligrams.
262 S. Burton et al. / Journal of Retailing 85 (3, 2009) 258–273
Table 2Study 1: Effects of nutrition information exposure and meal calorie level on consumers’ evaluations and repurchase intentions.
*p < .05; **p < .01.a Calorie level is a between subjects factor for lower versus higher calorie meals based on fast food restaurant website information. Lower calorie meals are fast
food meals with less than 720 calories and high calorie meals exceed 1,030 calories.dent m
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b Nutrition exposure is a repeated measure variable for which the initial depennformation. The second assessment of the measure was taken subsequent to ex
c Numbers shown in the table are univariate F values; degrees of freedom for
o which calorie and nutrient levels of “fast food” meals varycross restaurants. Consequently, consumer accuracy measuresiffer across the retail chains, as well. For example, the accu-acy measure for fat ranges from −20.6 to +1.0 (for Arby’s andhic-fil-A, respectively), and from −361 to −110 for calories
for Burger King and Chic-fil-A, respectively).Many promotional activities conducted by quick service
estaurants suggest that gender is an important segmentationariable in this retail industry (Nayga 2000). Thus, potentialifferences between calorie and nutrient accuracy measuresor males versus females are also considered. A MANOVAas performed with accuracy of the calorie, fat, and sodium
stimates as dependent variables. Females’ estimates of calo-ies (M = −107 vs. M = −324, F(1,465) = 24.2), fat (M = −4.2 g.s. M = −14.7 g, F(1,465) = 23.4), and sodium (M = −777 mg.s. M = −1,320, F(1,465) = 34.1) were more accurate thanales. However, males consumed substantially larger meals
han females (M = 1,020 vs. M = 757 calories, F(1,465) = 57.0;< .001). This suggests a possible mediating role of objectivealorie and nutrient levels. To test this possibility, hierarchicalegressions were run with calories, fat and sodium accuracy asependent measures. When gender was the sole predictor, thereas a significant effect (p < .001) for all accuracy measures (con-
istent with the above mean differences). However, when mealalorie and nutrient levels were also included as predictors in theecond stage of the analysis, the effect of gender on accuracyor calorie, fat, and sodium all were nonsignificant, supportinghe mediating role of meal nutrition level.3
ffects of meal calorie level and exposure to objectiveutrition information
Given consumers’ underestimation of calories and negativeutrients, we next examined how objective information on meal
3 Mediation also requires (1) the independent variable to affect the mediatori.e., meal nutrition level) and (2) the mediator to affect the focal dependentariable (Baron and Kenny 1986). Results support both conditions. Similar tohe pattern of results reported by Wansink and Chandon (2006) for overweightonsumers, the calorie and nutrient levels of fast food meals purchased by maleshigher in calories, fat and sodium) were larger than by females, and these largereal sizes that substantially exceeded consumer expectations were associatedith reduced accuracy.
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easure was assessed prior to exposure to the objective fast food meal nutritione to the objective information.ivariate tests = (1,333).
alorie and nutrient levels impacted consumer evaluations. H1redicted a moderating influence of the objective meal calorieevel on the effects of exposure to objective nutrition informa-ion. To test this prediction, a repeated measures MANOVA waserformed. Meal calorie level was a between subjects factor withwo levels, lower calorie meals (calories less than 720; n = 167)nd higher calorie meals (calories greater than 1,030; n = 168),etermined by a tercile split (Richins and Dawson 1992). Theepeated measure factor consisted of evaluations both before andfter exposure to the objective meal nutrition information forhe five dependent measures (perceived calorie attractiveness,eight gain likelihood, heart disease likelihood, meal healthful-ess, and repurchase intentions).
As shown in Table 2, the multivariate interaction is significantF = 9.9; p < .001), and significant univariate interactions extendo four of the dependent measures. For meals lower in calories,here is a significant increase (t = 2.51; p < .01) in attractivenessfter exposure to nutrition information, while there is a substan-ial (and somewhat stronger) decrease in attractiveness for theigher calorie meals (t = −7.18; p < .001). A conceptually sim-lar pattern was observed for the perceived likelihood of weightain. As shown in Fig. 1, information provision does not influ-nce the likelihood of weight gain for the lower calorie mealst = −1.47; p > .05), but it does so for the higher calorie mealst = 2.42; p < .01).
Plots for perceived meal healthfulness and repurchase inten-ions are shown in Fig. 2. After exposure to information,he increase in perceived meal healthfulness is nonsignificantt = 1.01; p > .20) for the lower calorie meals, but the decreasen healthfulness is significant for the higher calorie mealst = −5.54; p < .001). Repurchase intentions decrease after infor-ation exposure, regardless of whether the meal calorie level is
igh or low (p < .01 for each). However, the difference is clearlyreater for higher calorie meals (p < .05). Thus, H1 is broadlyupported.
onfirmation/disconfirmation of expectations for lower andigher calorie meals
The previous analyses do not directly address the role ofonfirmation/disconfirmation of expectations on the dependenteasures. To explore this question, additional analyses were
erformed. For consumers who purchased higher calorie meals
S. Burton et al. / Journal of Retailing 85 (3, 2009) 258–273 263
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tet(sde(ctent with theory and work similarly for both lower and highercalorie meals.4
4 We performed this analysis using different splits on calories and disconfir-
ig. 1. Study 1: Interactive effects of nutrition information disclosure and calorlower) values for calorie levels indicate more favorable (unfavorable) evaluatncreased (decreased) likelihood.
based on a median split, M = 1,222), we created groups that (1)nderestimated actual calories by 200 calories or more (initialxpectations disconfirmed) and (2) estimated calories to be equalr greater than actual levels (initial expectations confirmed).imilarly, consumers who purchased lower calorie meals (basedn a median split, M = 591 calories), were placed into one of tworoups. One group underestimated calories by 200 calories orore (expectations disconfirmed) and the other group estimated
alories to be equal or greater than the actual levels (expectationsonfirmed).
We then performed a 2 (confirmation or disconfirmation ofalorie expectations) × 2 (nutrition information disclosed or notisclosed) × 2 (higher or lower calorie level) mixed MANOVAo assess how the interaction between expectations and nutritionnformation disclosure affects the dependent measures. If theffects of this interaction are consistent across the two meal calo-ie levels (i.e., two- and three-way interactions involving mealalorie level are nonsignificant), this suggests that expectationsork similarly across both higher and lower calorie meals.Results show that the three-way multivariate interaction is
onsignificant (F = 1.77; p > .10) and the expectations by mealalorie level two-way interaction is also nonsignificant (F = 1.68;
> .10). However, the two-way multivariate interaction for nutri-
ion information disclosure by expectations (F = 4.90; p < .01)nd for nutrition disclosure by calorie level (F = 6.38; p < .01)re significant as well as the main effect for information dis-
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el on perceived calorie attractiveness and weight gain likelihood. Note: Higherhigher (lower) values for the perceived likelihood of weight gain indicate an
losure (F = 7.87; p < .01). The univariate two-way interactionetween nutrition information disclosure and expectations is sig-ificant for perceived calorie attractiveness (F(1,422) = 14.95;< .01), product healthfulness (F(1,422) = 17.67; p < .01), heartisease likelihood (F(1,422) = 5.97; p < .01), and weight gainikelihood (F(1,422) = 8.71; p < .01); results were nonsignificantor repurchase intentions (p > .20).
Two plots are shown in Fig. 3 for the confirma-ion/disconfirmation by disclosure interaction. Generally, and asxpected, disconfirmation (actual calorie level exceeds expecta-ions) has a negative impact on perceived meal healthfulnessF(1,268) = 34.73; p < .01) while confirmation has a somewhatmaller positive impact (F(1,156) = 4.62; p < .05). In addition,isconfirmation increases the perceived likelihood of heart dis-ase (F(1,268) = 13.27; p < .01) while confirmation has no effectF(1,156) < 1). The pattern of results suggests that the effects ofonfirmation or disconfirmation of expectations appears consis-
ation/confirmation levels and results follow the same general pattern. We alsoan two separate analyses where we split the sample into two groups, one withower calorie meals and one with higher calorie meals, and results are consistentith the analyses showing the nonsignificant interactions for meal size reported
n the text.
264 S. Burton et al. / Journal of Retailing 85 (3, 2009) 258–273
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tudy 1 discussion
Findings from Study 1 illustrate that consumers have a poornderstanding of the calorie, fat, and sodium levels of manyeals purchased at popular quick service restaurant chains (cf.ansink and Chandon 2006). Also, while small sample sizes
nd self-selection issues should be considered, the differencesetween retail restaurant chains suggest that some chains woulde in a better position to respond to mandated nutrition infor-ation disclosures.Results also indicate that exposure to the objective nutri-
ion information tends to decrease overall product evaluations.he general pattern of findings supports the contention thathile qualitative differences between fast food purchases are
ecognized by consumers, they have a limited understandingf their quantitative differences. Without awareness of thesectual quantitative calorie, fat and sodium levels, the potentialffect that quick service restaurant purchases may have on con-umers’ weight maintenance or weight loss efforts (which inurn may influence their long term health) appear difficult tossess.
However, when consumers become aware of meal caloriend nutrient levels, their product evaluations are influenced in
predictable manner. When objective calorie levels are rel-
tively low, estimates, on average, are very close to actualevels. Therefore, nutrition information provision has little influ-nce on consumers’ evaluations (as shown in Figs. 1 and 2).
csca
orie level on perceived meal healthfulness and repurchase intentions.
n contrast, when expectations are disconfirmed by informa-ion disclosure (i.e., when there is a significant level of calorienderestimation), product evaluations decrease. These findingsuggest that restaurant chains which serve foods with caloriend nutrient levels that substantially exceed consumers’ expec-ations may have cause for concern as nutrition informationisclosures on menus and menus boards become more widelyandated.The diary methodology offers potentially useful findings for
onsumers, policy makers, and restaurant retailers, but the expo-ure context (obtaining meal information online) is atypicalf how nutrition information would be presented if requiredhrough legislation. Also, there is no explicit control group, aimitation of the quasi-experimental design used. To narrow thisontextual gap, enhance internal validity, and extend tests of theisconfirmation framework, Studies 2 and 3 employ menu-basedxperiments to assess potential effects of calorie disclosure.
Study 2
The primary purpose of Study 2 was to determine, using aontrolled experiment, how the provision of objective calorienformation for actual quick service restaurant items influences
onsumers’ choices and purchase intentions. In Study 1 con-umer purchases were not controlled (i.e., they were actualonsumer purchases), and there was no explicit control group. Inddition, the purchased meals generally had calorie levels that
S. Burton et al. / Journal of Retailing 85 (3, 2009) 258–273 265
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ig. 3. Study 1: The interaction of the nutrition information disclosure and expunfavorable) evaluations; higher (lower) values for the perceived likelihood of
ere either above expectations or closely matched expectations.hus, under such circumstances negative disconfirmation andonfirmation, respectively, are likely to occur. However, manyetail chains offer a few very low calorie items on their menus.or these items, nutrition information provision should result inositive disconfirmation (cf. Woodruff and Gardial 1996). Thats, if consumers overestimate actual calorie levels, then objectivenformation should have a positive effect on purchase intentionnd choice.
2. The effects of a menu-based calorie information disclosureill be moderated by the extent to which consumers’ expecta-
ions deviate from actual levels. Specifically:
2a. When actual disclosed information on the menu is morenfavorable than consumers’ expectations (negative disconfir-ation), information provision will decrease purchase intentions
nd choice.
2b. When the information is more favorable than consumers’xpectations (positive disconfirmation), information provisionill increase purchase intentions and choice.
2c. When the information on the menu is consistent withxpectations (confirmation), there will be no effect on purchasententions and choice.
wdta
ons. Note: Higher (lower) values for meal healthiness indicate more favorabledisease risk indicate an increased (decreased) likelihood.
tudy 2 method
Predictions were examined using a 2 (menu calorie dis-losure: none (control) vs. calories present) × 3 (consumerxpectations: confirmation, negative disconfirmation, positiveisconfirmation based on the actual calorie levels of three menuptions) × 2 (retail chain: Burger King vs. Subway) mixedesign. Information disclosure was a between subjects fac-or, while the actual fast food items pilot tested and selecteds exemplars of the confirmation/disconfirmation of consumerxpectations and the retail chain were within subjects factors.he confirmation/disconfirmation of consumer expectations wasperationalized through the actual calorie levels (obtained fromebsites) of three different menu items. Pilot tests (that were
onfirmed in the main study) were used to determine calorieevel expectations for each of the menu items, indicating thatxposure to actual calorie levels on a menu would either con-rm or disconfirm these initial expectations. Pilot tests suggested
hat the Burger King (BK) Whopper with cheese and SubwaySW) 12 in. Turkey Sub Sandwich with cheese value meals hadalorie levels that substantially exceeded expectations (nega-ive disconfirmation) while the BK Tendergrill Garden Salad
ith medium diet drink and the SW Club Salad with mediumiet drink had calorie levels that were below consumer expecta-ions (positive disconfirmation). The BK Whopper Jr. value mealnd the SW 6 in. Turkey Sub Sandwich with cheese meal had
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alorie levels that were relatively consistent with expectationsconfirmation).
Thus, descriptions of three menu items from two nationalestaurant chains, Burger King and Subway, served as stimuli.hese retailers were selected because of their high nationwide
evel of familiarity and because of the discrepancy betweenctual and estimated calorie and nutrient levels found in Study. Prior usage and dining frequency were similar for bothestaurants. Ninety-seven percent of Study 2 participants hadined at each of the two restaurants in the past, and approxi-ately one-half of the participants reported dining at BK (49
ercent) and SW (55 percent) in the past month (all differ-nces are nonsignificant). The Burger King options that serveds exemplars of differing meal calorie expectations were asollows: (1) Whopper with cheese, large fries, and large reg-lar drink; (2) Whopper Junior, medium fries, and mediumiet drink; and (3) Tendergrill Garden Salad with mediumiet drink. The exemplar meals from Subway included: (1)2 in. Turkey Sub Sandwich with cheese, Classic Lays Potatohips, and large regular drink; (2) 6 in. Turkey Sub Sand-ich with cheese, Baked Lays Potato Crisps, and medium dietrink; and (3) Subway Club Salad with medium diet drink.5
he menu items were presented in several different orders onhe stimuli; analyses revealed that presentation order did notffect any dependent measures. Order of the presentation of theenus and measures for each restaurant also were counterbal-
nced.Participants were 363 adult consumers that are part of a web-
ased consumer panel (53 percent female; median age = 47).articipants were e-mailed a link to an online web survey. Theurvey contained the mock menu board stimuli and depen-ent measures. The menu boards presented descriptions of eachption based on information obtained from the retailers’ cor-orate websites. For example, the Subway Club salad wasescribed as follows: “sliced turkey breast, roast beef, hamnd your choice of vegetables on a bed of lettuce.” Each par-icipant was presented one version of the menu (items withescriptions that either did or did not include calorie infor-ation). Purchase intention for each of the six menu itemsas assessed by two, seven-point scales (endpoints of notrobable–very probable and not likely–very likely; coefficientlphas for this measure for each of the menu items rangedrom .97 to .98). Consumers were also asked to choose onef the items from each menu. To corroborate the confirmationnd disconfirmation of expectations, control group participantsi.e., those not presented calorie information) estimated thealorie levels of each item after completing the dependenteasures.
5 The objective calorie levels used for the menu items in the calorie dis-losure condition for Burger King were as follows: Whopper with cheeseeal = 1550 calories; Whopper Junior meal = 730 calories; and Tendergrill Saladeal = 240 calories. In the calorie disclosure condition for Subway, calorie
evels used were: 12 in. Turkey Sub meal = 1080 calories; 6 in. Turkey Subeal = 430 calories; and Subway Club Salad meal = 150 calories.
awWic(ttH
ling 85 (3, 2009) 258–273
tudy 2 results
hecks on the items as exemplars ofonfirmation/disconfirmation of calorie expectations
To support the three levels of confirmation/disconfirmation ofxpectations, analyses of variance followed by a series of t testsompared the differences between estimated and actual calo-ie levels for participants in the control condition. As desired,he Burger King Whopper with cheese meal and the Subway2 in. turkey sub with cheese meal resulted in negative dis-onfirmation. Calories of the Whopper and Subway 12 in. subeals were underestimated by 464 (30 percent underestimation)
nd 357 (33 percent underestimation) calories, respectively. talues assessing differences between expectations and objec-ive values are significant (t values = −8.6 and −9.9, p < .001).stimates for items used to confirm expectations were gen-rally accurate (−16 and +8 calories for the Whopper Jr.nd 6 in. turkey sub meals) and were not significantly differ-nt from 0 (t values = −.5 and +.4, respectively, p > .50). Asxpected, calorie levels of both salads were overestimated result-ng in positive disconfirmation. For the Burger King Tendergrillalad, consumer estimates were 196 calories higher than thebjective level (t(165) = +8.2, p < .001). The estimate for theubway Club salad exceeded the actual level by 195 calo-ies (t(164) = +9.1, p < .001). The pattern of results indicateshat these food items are appropriate exemplars for tests of2.
ffects on purchase intentionsA mixed ANOVA was performed to determine how the pro-
ision of nutrition information influenced purchase intentions.he interaction between item expectations and calorie disclo-ure is significant as predicted in H2 (F(2,722) = 7.90, p < .001).nteractions involving differences between the two chainsere nonsignificant (three-way interaction between restau-
ant, disclosure and expectations (F = 1.22, p > .25); restauranty disclosure two-way interaction (F = 1.32, p > .20)). Whilehe restaurant by disclosure interaction is nonsignificant, forlarity, plots of the means relevant to the predicted H2nteraction are presented separately for each retail chain inig. 4. When calories are not presented, purchase intentionsor both the Burger King and Subway meals with higherhan expected calories (negative disconfirmation) do not sig-ificantly differ (p > .30) from purchase intentions for mealsith lower than expected calories (positive disconfirmation).owever, there are significant differences in purchase inten-
ions when calorie information is disclosed. Specifically, whenegative disconfirmation occurs, the results of a contrastnalysis indicate that purchase intentions are lower (higher)hen calories are (are not) disclosed (F(1,370) = 3.98, p < .05).hen expected calories exceed actual calories, resulting
n positive disconfirmation, purchase intentions are signifi-antly higher (lower) when calories are (are not) disclosed
F(1,370) = 9.40, p < .01). When calories confirm expectations,he contrast for the differences between the calorie informa-ion conditions is nonsignificant (F < 1). These results support2a–H2c.
S. Burton et al. / Journal of Retailing 85 (3, 2009) 258–273 267
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Fig. 4. Study 2: Effects of nutrition information disclosure and confirmation
ffects on choice of itemsConsistent with the findings for purchase intentions, results
f a logistic regression analysis showed that the information dis-losure and restaurant interaction did not influence the choiceetween low and high calorie items (p > .30). However, as pre-icted in H2, the effect of the disclosure on choice differedor items that deviated positively and negatively from expecta-ions. Across the two restaurants, when positive disconfirmationccurred, the percentage of consumers who chose these loweralorie meals increased from 25 percent to 34 percent (z = 2.70,< .01). In contrast, when the provision of calorie information
esulted in negative disconfirmation, the percentage of con-umers who chose the high calorie meals decreased from 36ercent to 25 percent (z = −3.34, p < .01). Choice was not influ-nced when expectations were confirmed (p > .10). Plots of thesehoice data for both positive and negative disconfirmation con-itions and for each restaurant are shown in Fig. 5. The pattern
s significant across both restaurants.6
In general, although the methodologies used in this studya controlled experiment with mock menu) and in Study 1 (a
6 As can be inferred from the pattern of findings in Fig. 5 and consistent withhe results for purchase intentions, when the calorie expectations were confirmedor the items with moderate levels of actual calories, the disclosure of caloriesid not have a significant effect (z = 0.60; p > .30) on choice for these items.
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onfirmation on purchase intentions for quick service restaurant food items.
urvey and food diary) differed, a similar pattern of moder-ted effects were found. However, since actual menu items fromuick service restaurants were used, calorie levels for each ofhese specific items remained constant and thus do not offer atrong test of the effect of individual-level expectations. That is,ecause calorie expectations were not directly manipulated, its difficult to distinguish the effects of disconfirmation from theffects of the specific item calorie levels. To extend these find-ngs, Study 3 explicitly manipulates calorie expectations in ordero further address the influence of confirmation/disconfirmation.
Study 3
tudy 3 method
Study 3 employed a longitudinal experiment in which partic-pants first formed expectations regarding calorie levels and thenere provided product information that either confirmed or dis-
onfirmed these initial expectations (cf. Naylor et al. 2008). Toreate calorie expectations, participants were initially presentedith a fictitious restaurant review (developed by the researchers)
or Johnny’s Restaurant. The review described a meal consistingf a hamburger, French fries, and soft drink and created eitherigher or lower calorie expectations. To create low (high) calo-ie expectations, the review informed participants that almost
268 S. Burton et al. / Journal of Retailing 85 (3, 2009) 258–273
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ig. 5. Study 2: Effects of nutrition information provision and confirmation/disclower) values in plots for calories and purchase intentions indicate more favorancreased (decreased) likelihood.
ll menu entrees had less than 700 calories (at least 1,400 calo-ies).
In the second stage of the experiment (conducted on theollowing day), participants were asked to imagine that theyere in a food court at lunch and had been presented a menu
hat provided calorie information for several different ham-urger meals. Menu options included the hamburger meal fromohnny’s Restaurant (i.e., the fictitious restaurant described inhe review presented on the previous day). Calorie level of theohnny’s meal was either low (700) or high (1,400). This resultedn the following four conditions: (1) confirmation of high caloriexpectations (i.e., high calorie meal expectations are confirmedy the high calorie level presented on the menu); (2) confirma-ion of low calorie expectations (i.e., low calorie expectationsre confirmed by low calorie level); (3) positive disconfirmationf high calorie expectations (i.e., high calorie expectations areisconfirmed by low calorie level on the menu); and (4) nega-ive disconfirmation of low calorie expectations (i.e., low caloriexpectations created by the review are disconfirmed by the highalorie level on the menu). This scenario was meant to looselyorrespond to market conditions in which consumers have ini-ial expectations from prior experience that are either confirmedr disconfirmed by a subsequent exposure to objective calorienformation on a menu or menu board. Dependent measuresere assessed both after consumers read the review and again
fter the menu was presented. This created a mixed design withwo between subjects factors (high and low calorie expectationsither confirmed or disconfirmed) and a within subjects factormeasures assessed before and after calorie disclosure).
A pilot test was initially used to examine the effectiveness ofhe restaurant review and calorie levels in creating the desiredevel of meal calorie expectations. All aspects of the reviewere invariant except for information relating to the creationf calorie expectations. An initial pilot test indicated that theeview worked as desired. Manipulation checks in the main studyonfirmed the effectiveness of the review in creating the desirednitial expectations. Specifically, main study participants were
sked near the end of the final data collection, “Based only onhe restaurant review that I had read, I expected the calorie levelf the burger meal (hamburger, order of fries and a mediumrink) at Johnny’s to be . . ..” (seven-point scales with endpoints
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ation on reported choice for quick service restaurant food items. Note: Highernfavorable) evaluations; higher (lower) values for heart disease risk indicate an
f ‘very low’ and ‘very high’; ‘small’ and ‘large’; ‘much lowerhan normal’ and ‘much higher than normal’). Coefficient alphaas .93.Main study participants were 92 undergraduate students
ho participated for extra credit. Primary dependent variablesncluded a multi-item calorie evaluation of the Johnny’s com-ination meal (similar to Study 1), likelihood of heart diseasef the meal was eaten on a regular basis (single item), and pur-hase intentions. Reliabilities for calorie evaluation were .97 inoth the first and second stages of the study. Purchase inten-ions also had acceptable reliability (r = .78 in both stages). Thetudy also included measures to assess respondents’ hypothesisuessing, social desirability (Marlowe-Crowne measure), andocially desirable eating behavior.
tudy 3 results
nitial data checksAn ANOVA on the manipulation check variable indicated that
he review created a significant difference in the expectations ofeal calories (high and low calorie expectations means = 6.0
nd 4.2, F(1,84) = 48.4, p < .001), as desired. The manipulationid not affect the perceived taste of the meal (p > .10). Analy-es involving the measures used to assess hypothesis guessing,ocial desirability, and socially desirable eating behavior sug-est that hypothesis guessing and social desirability biases areot influencing the results. Regarding hypothesis guessing, onlyne respondent offered a description that was close to the pur-ose of the study. For the measures of social desirability, weound that the interaction between the menus (high or low calo-ie level) and measures of social desirability and social desirableating were not significant for any of the dependent variablesFs < 1, ps > .50).
ests of confirmation/disconfirmation of caloriexpectations
To address effects on the perceptions of meal calorie favora-ility, purchase intentions, and heart disease likelihood, mixed
NOVAs were performed. The key research question focusesn the confirmation/disconfirmation of expectations for mealsoth lower and higher in calories, indicating an interaction.or perceived calorie favorability, the interaction is significant
S. Burton et al. / Journal of Retailing 85 (3, 2009) 258–273 269
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ig. 6. Study 3: Effects of confirmation/disconfirmation on meal evaluations. Navorable (unfavorable) evaluations; higher (lower) values for heart disease risk
F(3,88) = 11.07, p < .01), as shown in the upper portion of Fig. 6.s seen in the plot, after the menu disclosure disconfirms the
avorable expectation created by the restaurant review, calo-ie favorability decreases (Ms = 4.56 vs. 3.14; F(1,25) = 16.61,< .01). This is consistent with the disclosure resulting in aegative disconfirmation of expectations. In contrast, whenhe review created higher calorie expectations which were notonfirmed because meal calorie level was low (i.e., positiveisconfirmation), there is an increase in perceived calorie favor-bility (Ms = 2.20 vs. 3.20; F(1,28) = 11.31, p < .01). When theenu calorie disclosure confirms high calorie expectations cre-
ted by the review, mean perceptions are unfavorable and remainonsistent (Ms = 1.97 vs. 2.13; F(1,20) = .19, p > .20). Somewhaturprisingly, for these data, confirmation of low calorie expecta-ions resulted in a significant increase in perceived attractivenessMs = 3.49 vs. 4.41; p < .05).
The purchase intentions interaction is significant
F(3,88) = 4.54, p < .01). The plot of means in Fig. 6 shows aattern similar to that found for calorie favorability perceptions.hen the menu disclosure (negatively) disconfirms the low
alorie expectation created by the review, purchase intentions
edlc
igher (lower) values in plots for calories and purchase intentions indicate moreate an increased (decreased) likelihood.
ecrease (Ms = 5.83 vs. 4.84; F(1,25) = 13.67, p < .01). When aigher calorie expectation created by the review is disconfirmedy low calories (i.e., positive disconfirmation), the differenceetween means does not reach significance (Ms = 4.59 vs. 5.07;(1,28) = 2.14, p = .15). When expectations are confirmed by
he disclosure, the means are consistent and there is no effect onurchase intentions, regardless of the meal calorie level (Fs < 1,> .50).
For the heart disease likelihood measure, the interaction isgain significant (F(3,88) = 4.19, p < .01), and the plot is shownt the bottom of Fig. 6. When a higher calorie expectation createdy the review is disconfirmed by a low meal calorie level on theenu (i.e., positive disconfirmation), the perceived likelihood
f heart disease is reduced (Ms = 7.71 vs. 6.71; F(1,28) = 7.13,< .02). When the menu disclosure (negatively) disconfirms the
ow calorie expectation created by the review, heart disease is notffected (Ms = 6.54 vs. 7.11; F(1,25) = 2.20, p = .15). When the
xpectations created by the review are confirmed by the menuisclosure, there again is no effect on disease likelihood, regard-ess of whether the hamburger and French fries combo mealalorie level is low or high (Fs < 2.0, p > .20).
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70 S. Burton et al. / Journal of
Within this experimental context, results indicate that when aow calorie disclosure is consistent with expectations, the (low)alorie level disclosed on the menu may lead to changes in mealalorie evaluations but not purchase intentions or perceived dis-ase likelihood. In retrospect, this is not surprising since mealalorie evaluations is the measure most likely to be impactedy objective calorie level. Although results did not reach sig-ificance in the positive disconfirmation condition for purchasententions or in the negative disconfirmation condition for like-ihood of heart disease, the results for both were in the expectedirection. In sum, as shown in Fig. 6, the overall pattern of resultscross the three dependent variables was generally consistentith predictions.
General discussion
Using an expectancy disconfirmation theoretical framework,he goal of this research was to provide a better understandingf how consumers’ product evaluations and purchase behaviorsithin the context of quick service restaurants are influenced byoth (a) the lack of easily accessible nutrition information andb) the provision of objective nutrition information. Given theimeliness and importance of this issue (Horovitz 2008; Rabin007), we discuss the potential implications of our findings foronsumers, retailers, and public policy makers.
Results indicate that consumers generally are poor estimatorsf the actual fat, sodium, and calorie content of many of theiruick service restaurant food purchases. This is particularly trueor foods that are relatively high in calories and negative nutri-nts. Replicating recent findings (e.g., Chandon and Wansink007a; Wansink and Chandon 2006), Study 1 results show thathe majority of consumers underestimate the calorie levels ofheir fast food purchases. We extend these recent results to dif-erent restaurants and purchase contexts, while also showing thats the levels of fat and sodium increase, underestimation of theseutrient levels increases as well.
Using a diary and surveys in Study 1, exposure to objectivealorie and nutrient information, as expected, had a negativesomewhat positive) impact on consumers’ perceptions and eval-ations of higher (lower) calorie and fat meals. Furthermore,he results of the menu board experiments in Studies 2 and
further demonstrate the critical role of deviation from con-umer expectations. When objective calorie levels were higherlower) than expected, purchase intentions were lower (higher).erhaps more importantly, compared to the no calorie disclo-ure control condition, the percentage of consumers choosinghe less healthful menu items decreased when actual caloriesere disclosed and exceeded expected levels, and the percent-
ge of consumers choosing the more healthful items increasedhen actual calories were disclosed and levels were less than
xpected.
mplications for restaurant retail management
Mandates requiring the provision of calorie information onenus and menu boards are scheduled to go into effect soon in
everal major U.S. cities, and will be going into effect for the
d
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ling 85 (3, 2009) 258–273
ntire state of California on January 1, 2011. Similar regula-ions appear to be on the horizon in a number of states and citiescross the country, and menu labeling requirements are the focusf the LEAN Act, which was introduced in September 2008 inhe U.S. Congress. Consequently, our results may help informhe decision making processes of managers within the quickervice restaurant industry as they adapt to the changing marketnvironment. As shown in Study 1, consumers generally under-stimate calorie and nutrient levels of quick service restauranturchases, and subsequent exposure to objective informationecreases reported repurchase intentions. However, there is sub-tantial variance in both the estimated and actual calorie andutrient levels across specific restaurants (e.g., Table 1) andcross menu items. These data suggest that some restaurants areurrently in a more favorable competitive position to mount aarket response to mandated nutrition information disclosures.onversely, quick service restaurants with signature items thatre substantially less healthy than consumers’ expectations maye in a somewhat less favorable position. Consistent with find-ngs from our studies and arguments from advocates in favorf menu labeling, some restaurants may wish to improve theirortfolio of healthy items by either introducing new products ormproving the nutrition profile of foods on their current menu bywitching to lower calorie ingredients. Similarly, serving sizesf the less healthful menu items could also be reduced while theizes of more healthful items (e.g., fruit, salads/vegetables withow calorie dressings or sauces) could increase volume with-ut sacrificing satisfaction with meal size. Results indicate thatt would also be useful for the chains to understand consumers’urrent calorie expectations for the full range of menu items thatre offered. In addition to introducing healthier items, for someigher calorie items restaurants may want to explore ways toncrease consumers’ expectations so that they do not experiencetrong disconfirmation effects when disclosures occur.
Most quick service restaurants offer consumers’ some lowalorie options (e.g., salads and grilled chicken sandwichesffered by Burger King and McDonald’s), and results show thatalorie disclosure can result in positive disconfirmation that mayead to an increase in purchases. Although the availability ofhese more healthful items may help diffuse some customers’egative reactions to the disclosure of objective calorie and nutri-nt information that is higher than expected, for the segmentf consumers most concerned about diet and nutrition, “calorieticker shock” may be a likely response (Rabin 2007). Such reac-ions may be amplified by the contrast between very low and veryigh calorie items (e.g., 240 calories in a Burger King Tenderrill salad and diet drink compared to 1,510 calories for a Dou-le Whopper and large shake). Further research is warranted; ofarticular interest is how store patronage and food choices areikely to be influenced by the provision of calorie information forn entire menu of a chain (Pan and Zinkhan 2006). For a givenhain, if expectations are primarily confirmed, few changes inhoices or patronage would be anticipated due to the calorie
isclosure.
Mandated nutrition information disclosure also provides anpportunity for more refined market segmentation. Results sug-est that restaurants such as Chic-fil-A may be in a position to
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S. Burton et al. / Journal of
ore strongly promote the relative healthfulness of their pri-ary fare, compared to consumer expectations. There appears
o be a health conscious segment of consumers who state thathey will dine out more frequently if easily accessible nutri-nt and calorie information is available (Rabin 2007). Thisay be reinforced for items that lead to positive disconfirma-
ion, as suggested in Studies 2 and 3. When selecting a meal,aste is often the most important consideration. However, themportance of taste, relative to product healthfulness, is moremportant for some segments than for others (e.g., Glanz etl. 1998). One option some restaurant chains may consider isargeting young (male) consumers through use of light-heartedampaigns that flaunt taste while emphasizing the lack of mealealthfulness.
Although an environment of nutrition disclosures potentiallyffers marketing opportunities for some firms with relativelyutritious fare, our findings do raise some concerns for theseetailers. The product positioning used in Subway’s advertis-ng (i.e., strongly emphasizing their low fat menu items) seemso have created a health halo effect (Chandon and Wansink007a). For example, Study 1 findings suggested that, on aver-ge, estimated fat levels (11 g) are almost 50 percent lowerhan the actual fat (20.7 g) levels at Subway. Exposure to val-es for less healthy options may result in dissatisfaction forome consumer segments. In addition, awareness of the potentialffects of health halos might provide consumers with importantnformation that enhances consumers’ specialized knowledgeegarding fast food marketing communications (Friestad and
right 1994; Hardesty, Bearden, and Carlson 2007). Note thathis halo effect is particularly large for sodium; the promo-ion may lead consumers to anticipate lower levels of sodiumor Subway meals but the processed meat used in many sand-iches leads to sodium levels comparable to the hamburger
hains.
mplications for consumers and public policy makers
This series of studies is an example of retailing researchhat addresses a policy-relevant consumer behavior issue (cf.rewal and Levy 2007), and findings are likely to be of inter-
st to both consumer researchers and policy makers. The risingrevalence of both childhood and adult obesity is a signifi-ant national health problem that, despite widespread mediattention and high consumer awareness of the health risks asso-iated with overweight and obesity, shows few signs of abating.uccessful weight loss depends on many factors. However, inany cases, the key to losing weight is to consume fewer
alories than are expended; consumption of 3,500 more calo-ies than are expended is expected to increase weight by oneound. Results from Study 1 show that, on average, partic-pants were unknowingly consuming 900 extra calories in aeek from restaurant meals. This degree of underestimation
ppears capable of causing significant weight gain over the
ong term. Clearly, there appears to be a potential ‘cost ofgnorance’ (Forster and Just 1989) associated with not makinghe nutritional values accessible for meals prepared outside theome.
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ling 85 (3, 2009) 258–273 271
Given the direct role calorie consumption can play in theevelopment of obesity and overweight, health professionalsnd public policy makers have emphasized the importance ofalancing calorie intake with energy output. However, over-onsumption of nutrients such as sodium can also have aetrimental effect on health and contribute to the developmentf cardiovascular (or other) disease. Approximately 77 per-ent of sodium consumed on a daily basis is obtained fromestaurant and processed foods. (Note that in Study 1, consump-ion of sodium was underestimated by more than 1,000 mg.)ome have suggested that reducing salt consumption by one-alf may save more than 150,000 lives each year in the Unitedtates (Alonso-Zaldivar 2007). For consumers with health con-itions that make sodium an important concern, these resultsre alarming and suggest the importance of some form ofisclosure for consumers at risk for hypertension or heart dis-ase.
Our study findings provide some potential insight into whyery frequent restaurant diners may have difficulty maintainingr losing weight—the average consumer has very little knowl-dge of the total calorie and nutrient content of meals purchasedrom restaurant chains. Because of this lack of knowledge, con-umers are unable to make fully informed food choices. Makingalorie and nutrient information easily available to consumers athe retail point of purchase, rather than requiring an active infor-
ation search which is now the status quo, could potentiallyelp restrained eaters better manage their caloric and negativeutrient intake. For such health conscious consumers, nutri-ion information disclosures may also strengthen goal activatione.g., weight loss), which in turn, may encourage more goalirected behaviors (e.g., selection of a diet rather than a regularoft drink). However, nutrition disclosure programs only addressne aspect of the problem—the lack of easily accessible, accu-ate nutrition information. Information provision will not benefitonsumers who lack the motivation and desire to utilize thatnformation during their food selection processes (Howlett etl. 2009). A disclosure program in combination with a nutri-ion education campaign seems to offer the greatest potentialonsumer benefits.
imitations and implications for future research
Using methods commonly utilized in retailing researchBrown and Dant 2008), this research combined a diary andurvey data assessing consumption behavior with two menu-ased experiments; however, limitations remain that may restricthe generalizability of findings. In the experiments, consumersxamined nutrition information outside of the context of actualestaurants. When selecting items from a menu in actual restau-ants, situational and contextual differences may lead to differentesponses. It is difficult to obtain behavioral responses to fullutrition disclosure that mimics the actual market, with all ofts contextual influences, without the complete cooperation of
estaurant management. In addition, Study 1 lacked a controlroup, and this introduces potential threats to internal validity.ll studies focused only on quick service restaurants. However,oth pending and passed legislative initiatives also include provi-
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72 S. Burton et al. / Journal of
ions for table service restaurant chains. Because many of theseable service restaurants (e.g., Chili’s, TGI Friday’s) featureome very large servings of high calorie items, future researchay focus on specific restaurants in this category. In addition,andates passed in California, New York, and Seattle requiring
hain restaurants to disclose calories on menus and menu boardsill permit the collection of consumers’ responses in actualarket conditions. Such longitudinal field studies should be par-
icularly useful in overcoming many potential problems relatedo the generalizability of findings and specific implications forestaurant retailers. In addition, such results will serve to guideuture legislation (e.g., the recently proposed LEAN Act) aimedt helping reduce the prevalence of overweight and obesity, ateast among some segments of consumers by mandating the pro-ision of calorie and nutrient information for away-from-homeoods. Studies of differences in effects based on consumers’urrent health status and health goals and motivation is war-anted.
Consistent with these local and national labeling initiatives,he goal of this research was to address a substantive issue that isimely, relevant, and important. Given this substantive question,e acknowledge that the research generally was more concernedith the application of relevant theory rather than a more direct
oncern with the development of new theory per se (e.g., Mick005; Simonson et al. 2001). However, there are a variety ofuture studies that could address conceptually compelling topicselated to this menu labeling issue. For example, research couldxamine how nutrient estimates are formulated across differentestaurants and explore how specific factors (e.g., positioningtrategy, target markets, pricing) may affect the accuracy ofhese estimates across restaurants. In addition, is it possible for
andated nutrition information disclosure to have unintendedonsequences? For example, will some segments of consumershoose less healthy meal options because of psychological reac-ance or other reasons? In sum, there are many opportunities fordditional theoretical and applied research that would involvexperimental, longitudinal and qualitative methodologies forhis topic that has potentially important implications for aca-emics interested in retailing and consumer behavior issues, asell as for retail restaurant chain marketers.
Acknowledgements
The authors would like to thank the three anonymous review-rs and the Special Issue editors for their helpful comments anduggestions throughout the review process.
We gratefully acknowledge support for this research from theenter for Retailing Excellence and the Mark and Dayna Suttonaculty Support Fund, Sam M. Walton College of Business,niversity of Arkansas.
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