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Visual information influences consumer fast-food choices Kittipong Boonme Department of Decision Science, University of North Texas, Denton, Texas, USA

Bartlomiej Hanus Business Computer Information Systems, University of North Texas, Denton, Texas, USA

Visual information influences consumer 279 Received 2 March 2013 Revised 4 February 2014 Accepted 4 February 2014

Victor R. Prybutok Department of Decision Science, University of North Texas, Denton, Texas, USA

Daniel A. Peak Business Computer Information Systems, University of North Texas, Denton, Texas, USA, and

Christopher Ryan Department of Art and Science, University of North Texas, Denton, Texas, USA Abstract Purpose – The purpose of this paper is to investigate the influence of visual information cues such as a heart icon vs the calories and fat content on the selection of healthy food in fast-food restaurants (FFRs). Design/methodology/approach – An online survey design providing a fast-food menu was implemented to collect responses from the participants. The survey respondents were recruited from a large South-western university in the USA. The research model was tested using logistic regression. Findings – Data analysis shows that visual information plays a significant role in healthy food selection in FFRs. The authors findings show that the heart icons have a statistically significant effect on food choices, while calories and fat content information did not affect the participants’ selections vs no information. Originality/value – Dietary choices and obesity are a serious social concern. This study provides support for the effect of a heart icon symbol on food choice in fast-food selection. The implication is that labelling FFR menus with symbols such as our heart icon will have a positive impact on healthy food selection vs the more usual inclusion of calorie and fat information. Keywords Decision-making, Visual information, Calories information, Fat information, Health claims, Heart icons Paper type Research paper

Introduction Obesity is a critical health issue facing the USA because of its link to disease and the associated healthcare costs (Rashad and Grossman, 2004). Low-nutrition, high-fat,

Nutrition & Food Science Vol. 44 No. 4, 2014 pp. 279-293 © Emerald Group Publishing Limited 0034-6659 DOI 10.1108/NFS-03-2013-0036

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high-sugar and high-sodium fast-food contributes to obesity. Reports suggest that obesity will affect 30 million Americans by 2030 and increase health care expenditures by 549.5 billion (Finkelstein et al., 2012). Gallup poll has shown that obesity rates are increasing over time (Sharpe, 2013). Bowing to public pressure, many fast-food restaurants (FFRs) now provide healthier food alternatives for health-conscious customers. Nevertheless, the actual factors that affect customers’ food choices at FFRs remain vague. This study investigates this important issue by focusing on consumer food choices based on the restaurant menu presentation style (Hellmich, 2013). The goal of this study is to examine the factors affecting consumers’ food decision-making in an FFR. Multiple factors subjectively affect consumer choices, including but not limited to, convenience, taste and food quality. We measure these factors within a model that relates to individual food choices, specifically the impact of health icons and nutrition information on consumers’ food decisions. This research will benefit health practitioners and policymakers through insights that affect obesity in Americans. The results provide potential benefits to society in the form of recommendations to health practitioners about how to influence food choices, restaurant policy and an approach to assisting consumers in food choices that affect their health and weight. Evidence indicates that consumers consider health and nutrition information when making food decisions, such as searching or reading nutrition information and health claims at grocery stores (Balasubramanian and Cole, 2002; Moorman, 1996). Consumers use nutrition information when comparing similar products of different brands when making food purchases (Baltas, 2001). However, research shows the effect of nutrition information and health claims are still unclear to consumers (Ford et al., 1996; Garretson and Burton, 2000). There exist inconsistent findings about the effect of nutrition information on consumers (Teratanavat and Hooker, 2005). Currently, the Food and Drug Administration (FDA) allows packaged and restaurant menus to have nutrition and health claims (Kozup et al., 2003). Consumers usually can verify such health claims on packaged foods by checking the nutrition information (Kozup et al., 2003). However, a dilemma arises for consumers when these health claims accompany food served at restaurants, especially FFRs: they cannot easily verify the health claims due to a lack of nutrition information provided by the restaurants. For example, the nutrition information for a McDonald’s menu is available only online. Another problem is the lack of common definitions and standards with health claims between restaurants. For example, one restaurant could use an image such as a heart shaped icon to show low caloric value of a particular meal, while another restaurant could use a Weight Watchers symbol to show that a meal meets specific guidelines according to the Weight Watcher’s standards. Therefore, while some consumers attempt to use nutrition information (Baltas, 2001), the lack of standardization does not always allow for comparison. The current literature on the topic identifies several factors that affect healthy food choices in people, including, lifestyle, self-control, variety-seeking, weight control (diet), sensory appeal, perceived food quality, calorie and fat information and health claims. We operationalize the health communication using terms of heart icons on a menu and compare that to the use of fat and calorie information.

Methodology We define variety-seeking behaviour as the intrinsic desire for variety (Van Trijp and Steenkamp, 1992). There are two approaches to variety-seeking behaviour: (1) research stream views varied behaviour as an artefact of multiple needs or of changes in the choice problem; and (2) regards variation in behaviour as inherently rewarding. In food-related contexts, variety seeking is relevant to the short-term and long-term perspectives. The former one refers to sensory specific satiety – as the food is consumed; satiation for the sensory properties grows. The latter approach pertains to optimal stimulation level – individuals are believed to be seeking an optimal level of variation in their food choices (Lähteenmäki and Van Trijp, 1995). Individuals in adolescence period start to look for more variety in foods they consume, partly because of health and weight concerns. People affected by neophobia have higher intake of saturated fat and less food variety (Rubio et al., 2008). This condition appears to be a major issue for public health (Rubio et al., 2008). Therefore, we postulate the following: H1. Higher levels of variety seeking are positively related to healthy food choice from a fast-food menu. We define self-control as “the choice of a larger, more delayed reinforcer over a smaller, less delayed reinforcer” (Logue, 1988), based on two dimensions: self-control and impulsiveness. Our claim is based on previous research that depicts self-control as a multidimensional concept (Williams and Ricciardelli, 2000). The former is related to long-term orientation and ability to resist temptations. The latter is related to lack of self-control or impulsiveness. Overall, self-control is an important factor affecting healthy and desired behaviours, which makes self-control an important predictor of healthier food selection in FFRs. Higher levels of self-control also diminished impact of impulsiveness (Baumeister, 2002). Thus, individuals with high levels of self-control should be more successful in enforcing healthy dietary behaviours. Furthermore, individuals with high self-control generally have healthier eating patterns and lower BMIs. Thus, we develop the following hypotheses: H2a. Higher levels of self-control positively relate to healthy food selection from a fast-food menu. H2b. Lower levels of impulsiveness positively relate to healthy food selection from a fast-food menu. Natural content of food relates to the lack of additives (e.g. preservatives) and inclusion of natural (unprocessed) ingredients in food. Natural content of food may influence food choice, as health-oriented customers will seek for more healthy items on the menu. Therefore, natural content of food is related to healthy food selection (Steptoe et al., 1995). We believe that the content of food would lead to a selection of healthy food over unhealthy food. H3. Higher levels of natural content in food positively relate to healthy food selection from a fast-food menu. We propose that diet and weight control behaviours will have an impact on selecting healthy food over the unhealthy food. For example, young people tend to talk about food

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in terms of what they like and dislike, rather than what is healthy or unhealthy (Shepherd et al., 2005). Healthy food is predominantly linked with parents, while unhealthy food is associated with pleasure and social environments. However, young people perceive fast food to have a negative impact on weight and facial appearance, which served as a motivation to healthy eating. While they understand the importance of a healthy diet, taste preferences for fast foods tend to dominate food choice. Another study (Conner and Norman, 1996) shows that weight control behaviours (e.g. limiting intake at meals, avoiding fat, exercising, avoiding alcohol and avoiding snacks) are performed significantly more frequently, except exercising, when trying to control weight. Knäuper et al. (2005) suggests that the reduction of caloric intake was effective in achieving self-set dieting goals. Based on the previous research, we postulate the following: H4. Higher levels of dietary and weight control behaviours positively relate to healthy food selection from a fast-food menu. We define a food-related lifestyle as a system of cognitive categories, scripts and associative networks relating a set of food-related behaviours to a set of values. It is related to customs and habits related to food consumption. Thus, lifestyle serves as a vehicle for the values that people hold regarding health in our investigation – healthy eating. Yet, it is noteworthy that food-related lifestyle is not equivalent to the actual food-related behaviours (Brunsø and Grunert, 1998). Previous studies have shown that a healthy lifestyle is an important predictor of patterns in eating habits. Therefore, we postulate: H5. A healthy food-related lifestyle positively relates to healthy food selection from a fast-food menu. We purpose that intention and satisfaction to the consumers’ food choices leads to healthier food selections. Healthy intention leads to making healthy food choices (Weijzen et al., 2009). Previous studies have shown that intention leads to healthy food selection (Brug et al., 2006; Verbeke and Pieniak, 2006; Sparks et al., 2001). Research shows that consumers experience feelings of satisfaction when they select healthy food items (Saba and Vassallo, 2012). Satisfaction was the primary component that leads to the positive effect on the consumption of fruits and vegetables (Saba and Vassallo, 2012). Therefore, we postulate: H6a. Intention positively relates to healthy food selection from a fast-food menu. H6b. Satisfaction positively relates to healthy food selection from a fast-food menu. We investigate the effect of health claims on consumer food choice. Health claims are claims by manufactures that food products improve health or reduce the risk of developing a disease or condition. Based on previous research, we believe that health claims affect consumers’ food decisions. Health claims can cause consumers to have a positive product view. In addition, consumers might rely on the health claim instead of the nutrition information when making their food choices (Chandon and Wansink, 2007). Research has also shown that health claims in FFRs cause consumers’ to underestimation the caloric content. The research stream has led us to believe that health claims impact food decision in a healthy way.

H7. A heart icon positively relates to healthy food selection from a fast-food menu. We study the effects of visibility of calorie information on a menu on fast-food selection. Previous research suggests that calorie information can affect consumer decisions. For example, Bassett et al. (2008) show those consumers choose lower calorie food items when they are provided with calorie information. Research also shows that consumers are paying more attention to nutritional information, such as calories and fat on food products than they did in the past (Ippolito and Mathios, 1991). We believe that clearly stated calorie information will affect consumer food choice. We also propose that fat information will result in selecting healthy food over the unhealthy food. When fat information is clearly communicated, consumers understand its meaning and will use the information for decision-making (Jasti and Kovacs, 2010). Thus, we posit:


H8. Available calorie and fat information positively relates to healthy food selection from a fast-food menu. In total, 250 total survey responses were received from three different groups of respondents at a major south-western university, and 20 of those were deemed unusable because they were not completed. The demographic characteristics of the useable surveys showed that 40 per cent of respondents were females. Approximately 63 per cent were between the ages of 21 and 25 years. All respondents surveyed had dined at an FFR at least once or more in the last 7 days before completing the survey. The detailed sample statistics are provided in Table I. The survey instrument has been developed based on existing scales. The main objective of the survey was to learn more about consumer food choice when consumers are given nutritional and iconic information. We manipulated the independent variables such as nutritional information and heart icons on the fast-food menu. We randomly provided the respondents with one of three different menu types. The control group was given a menu with no heart icon or nutrition information. Two groups were given menus with partial information. One received a heart-icon only menu,

Categories Class year Freshman Sophomore Junior Senior Graduate Age (years) ⬍18 18–20 21–25 26–30 31–35 ⬎35 Gender Male Female

Count

Percentage

4 20 152 70 4

2 8 61 28 2

0 43 158 25 18 6

0 17 63 10 7 2

151 99

60 40

Table I. Demographic information of subjects

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while another received a menu with nutrition information only. The presence of heart icons was based on threshold calorie values associated with each item on the menu. For example, two heart icons were used for items with ⬍400 calories and one heart icon for entrees with ⬍1,000 calories. A web-based format consisting of two sections was used over the traditional paper survey because it allowed for richer interaction with the respondents. The first section asked respondents general information about their thoughts and attitudes towards FFRs. The second section gave a menu that looked similar to an FFR menu with the modification for the treatment being randomly assigned and asked respondents to make their food choices. Afterwards, the respondents were asked questions as appropriate for their treatment group such as the effect of the available nutrition or heart icon information on their food choice (Figure 1). Data analysis Table II includes the summary of the instrument used in this study, along with reliability analysis (Cronbach’s alpha). Chronbach’s alpha measures the internal consistency of the measurement items. All alpha values are above the recommended 0.7, except content of food. Content of food has Cronbach’s alpha equalled only to 0.664, which is below the generally accepted value. However, this reliability coefficient may decrease to 0.60 in exploratory research (Robinson et al., 1991) and was deemed acceptable for inclusion in this study. We conducted an exploratory factor analysis (EFA) on all the survey items from the questionnaire related to the measured constructs. We employed principal components extraction method using Direct Oblimin rotation with Kaiser Normalization. In addition, we conducted another factor analysis using Principal Axis Factoring extraction with VARIMAX rotation and Kaiser Normalization. In both cases, we have employed the latent root criterion to extract the factors, leaving only the factors whose eigenvalues were ⬎1 (Hair et al., 2010). For the oblique rotation, we report only the factor pattern matrix because as correlation among factors becomes greater, it is more difficult to distinguish which variables load uniquely on each factor in

Figure 1. Fast-food menu displaying calorie, fat and heart icon information

Item Number VS1 VS2 VS3 VS4 VS5 VS6 SC1 SC2 SC7 SC8 SC3 SC4 SC5 SC6 SC9 SC10 NV1 NV2 NV3 NV4 CoF1 CoF2 D1 D2 D3 LH1 LH2 LH3 PFQ1 PFQ2 PFQ3 PFQ4 PFQ5 S1 S2 S3 S4 I1 I2 I3

Item detail I am curious about food products that I am not familiar with I like foods from different countries I like to eat exotic foods Items on the menu that I am unfamiliar with make me curious I eat a wide variety of foods While eating at the FFR, I like to try out new cuisines I am good at resisting temptation I never allow myself to lose control People would say that I have iron self-discipline I am able to work effectively towards long-term goals I do certain things that are bad for me, if they are fun I have trouble saying no People would describe me as impulsive I do many things on the spur of the moment Sometimes I can’t stop myself from doing something, even if I know it is wrong I often act without thinking through all the alternatives The foods in the FFR contain a lot vitamins and minerals The foods in the FFR contain high nutritional value The foods in the FFR keep me healthy The foods in the FFR are high in protein The foods in FFR contain no additives The foods in FFR contain natural ingredients The food in the FFR helps me control my weight The food that I purchase from the FFR is usually low in calories The food that I purchase from the FFR is usually low in fat I avoid fat in the food I eat I limit my salt intake I follow a balanced diet The food on the menu looks fresh The food on the menu is well presented The food on the menu looks good The food on the menu looks pleasant The food on the menu looks nice I am satisfied with my food choice My food choice was a wise one I think I did the right thing when I made the food choice I feel that the ordering experience was enjoyable I intend to dine at this FFR in the future I will recommend this FFR to others If asked, I will say good things about this FFR

Cronbach’s alpha 0.897

Sources Adapted from (Van et al., 1992)


0.738

Adapted from (Tangney et al., 2004)

0.789

Adapted from (Tangney et al., 2004)

0.875

Adapted from (Steptoe et al., 1995)

0.664

Adapted from (Steptoe et al., 1995) Adapted from (Steptoe et al., 1995)

0.89

0.835

Adapted from (Steptoe et al., 1995)

0.937

Adapted from (Johns and Howard, 1998; Kivela et al., 1999)

0.852

Adapted from (Olorunniwo et al., 2006)

0.906

Adapted from (Boulding et al., 1993; Keillor et al., 2004)

Notes: VS–variety-seeking, SC–self control, NV–nutritional value, CoF– content of food, D–Diet, LH–lifestyle and habits, PFQ–perceived food quality, S–satisfaction, I–intention to dine

the factor structure matrix (Hair et al., 2010). Furthermore, some items (SC9 in oblique rotation, SC3 and SC8 in orthogonal) load barely ⬎0.4; however, factor loadings of this size are considered significant with the sample of ⱖ200 (Hair et al., 2010). Factor analysis provided some interesting findings. Satisfaction with the FFR and intention to dine in that FFR were loaded as separate factors, independent of the type of rotation used (Direct Oblimin vs VARIMAX). Furthermore, factor analysis confirmed

Table II. Survey instrument and reliability analysis of items

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that self-control is actually composed of two dimensions (factors) of a single construct, which is consistent with the literature review definition of self-control. SC1, SC2, SC7 and SC8 compose the first of the two factors that emerged from self-control items. Investigation of these items shows that they are related to self-control with the long-term orientation and ability to resist temptations. The second factor (SC3, SC4, SC5, SC6, SC9 and SC10) is related to the lack of self-control or impulsiveness. The results of this study are, in line, with the findings of Williams and Ricciardelli (2000), who claim that self-control is a multidimensional concept. Therefore, our research involves two constructs related to self-control, which we label self-control and impulsiveness, respectively. Somewhat surprisingly, items related to content of food and diet and weight control were loaded as one factor, even when using oblique rotation. Further examination of these items provides some insights. First, content of food items are related to natural vs artificial aspect of food content. The items on the diet and weight control scale refer to properties of food that are generally considered unhealthy in large amounts (e.g. fat and calories). However, all of these constructs pertain to the effect on an individual’s health and well-being from different perspectives. Although the two constructs loaded as one factor in our study (even when Direct Oblimin rotation was implemented), we decided to rely on prior research and keep them separate, so that we could see whether any of these different dimensions had a significant impact on selecting healthy food. Having established the reliability and validity of our instrument, we then conducted the test of our model and hypotheses. To assess the overall fit of our logistic regression model, we drew on three approaches: (1) statistical measures of overall fit; (2) pseudo-R2 measures; and (3) classification accuracy expressed by the hit ratio (Hair et al., 2010). Comparing to the base model, our research model has the ⫺2LL value reduced from 344.266 to 274.076, a decrease of 70.19 that is statistically significant at the 0.01 level. We have also estimated the overall fit of our model using the Hosmer and Lemeshow test, and our full research model had a significance level of 0.798, which indicates that the model fit is acceptable. Furthermore, Cox and Snell R2 and Nagelkerke R2 were 0.245 and 0.327, respectively. These values indicate that our model accounts for approximately one-third of the variation in the measure of Healthy Choice dependent variable. The third approach to overall model fit refers to assessing the classification accuracy of the model. The classification matrix presents the predictive accuracy achieved by a given model. Our model has correctly classified 72.4 per cent of participants. According to Hair et al. (2010), this level of accuracy is acceptable. Results Performing logistic regression on our research model allowed us to test the hypotheses. The results of the logistic regression are presented in Table III. We postulated (H1) that higher levels of variety seeking (B ⫽ 0.310, p ⫽ 0.017) will result in choosing healthy items over unhealthy ones on the menu. Our research model supports this hypothesis. H2 posited that higher levels of self-control would lead to selecting healthy items on the menu. However, EFA reveals that self-control was actually composed of two factors: self-control and impulsiveness. We tested

Construct measurement Variety-seeking Self-control Impulsiveness Content of food Diet Lifestyle and habits Intention Satisfaction Heart icon Calories and fat Constant

Beta

SE

p-value

Odds ratio

0.310 ⫺0.493 ⫺0.081 ⫺0.321 0.421 0.393 ⫺0.314 0.712 0.793 0.119 ⫺3.079

0.130 0.160 0.147 0.146 0.159 0.126 0.147 0.171 0.363 0.375 1.200

0.017 0.002 0.584 0.028 0.008 0.002 0.033 0.000 0.029 0.750 0.010

1.364 0.611 0.923 0.725 1.524 1.482 0.731 2.038 2.210 1.127 0.046

95 per cent CI for odds ratio Lower Upper 1.056 0.447 0.692 0.545 1.116 1.158 0.547 1.456 1.085 0.540

1.761 0.835 1.231 0.965 2.082 1.897 0.976 2.851 4.504 2.348

Notes: The dependent variable is a healthy food selection from the menu (either “yes” or “no”); Significant predictors at p ⬍ 0.05

each factor separately. As a result, self-control has a significant influence on healthy item selection (B ⫽ ⫺0.493, p ⫽ 0.002). However, the direction of relationship was surprising. Individuals with high levels of self-control are actually 38.9 per cent less likely to choose a healthy item than to select an unhealthy meal. On the other hand, impulsiveness does not significantly influence selection of a healthy item on the menu (B ⫽ ⫺0.081, ns). Thus, H2a and H2b are not supported, although self-control is significant but in the opposite direction as anticipated. These results may be related to the age and type of respondents involved, and generalization is not advised. Furthermore, individuals with strong self-control may make prior decisions about willingness to eat less healthy food on occasions when they go to FFRs. The results of EFA show that the items for measuring food content and diet loaded as one factor. However, closer examination of these items revealed that they actually referred to slightly different dimensions of the same factor. Therefore, we retained them as separate constructs. The logistic regression shows that content of food is significant (B ⫽ ⫺0.321, p ⫽ 0.028); however, it is in the wrong direction, as we initially proposed. Accordingly, our hypothesis, H3, is not supported. We postulated that diet (H4) will result in choosing healthy items. As a result, diet has a positive significant influence on healthy item selection (B ⫽ 0.421, p ⫽ 0.008). Furthermore, the results of the logistic regression support our claim that these items represent different dimensions of the same construct; therefore, they should be addressed as individual constructs. We have hypothesized that lifestyle and habits (H5) will positively influence the choice of a healthy meal. This postulate is fully supported (B ⫽ 0.393, p ⫽ 0.002). Also, both satisfaction (B ⫽ 0.712, p ⫽ 0.000) and intention to dine in FFR (B ⫽ ⫺0.314, p ⫽ 0.033) significantly influence selection of a healthy item on the menu. However, intention to dine in was significant but in the opposite direction, we initially predicted. Therefore, satisfaction is supported, whereas intention to dine in is not supported. Finally, we hypothesized that both the heart icon (B ⫽ 0.793, p ⫽ 0.029) and calories and fat information (B ⫽ 0.119, p ⫽ 0.75) will significantly affect the choice of a healthy meal from the menu.


Table III. Logistic regression analysis of healthy food selection in FFR

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Interestingly, participants exposed to a heart icon are more than twice as likely to select a healthy meal rather than to select an unhealthy one, with the odds ratio equal to 2.210. Furthermore, the heart icon was the most influential construct in selecting healthy food in our model. Hence, H7 is supported. On the other hand, calories and fat information was not significant with p-value of 0.887 – thus, H8 is not supported. The summary of hypotheses testing results is included in Table IV. Discussion Our goal was to investigate whether heart icons can influence selecting healthy food in FFRs and our results showed they were. At the same time, calories and fat information were not found to be a significant factor in the decision to select healthy food. We posit that customers who visit FFRs need to order their food quickly, and the heart icon may provide fast information about the content of food presented on the menu. Alternatively, perhaps customers do not have sufficient knowledge to determine how healthy the food is based on the calories and fat information provided (Higginson et al., 2002). Nevertheless, using heart icons on a fast-food menu leads to higher probability of ordering healthy food than ordering unhealthy selections, which is in line with previous studies on health claims (Chandon and Wansink, 2007; Roe et al., 1999). Still, further research should be conducted on this matter, preferably including other audiences than college students. Contrary to our expectations, the results suggest that a high level of self-control results in decreasing odds for choosing a healthy item over an unhealthy one. We propose that customers who demonstrate high levels of self-control are aware of the quality of food available in FFRs and that their choice to eat in such a restaurant was made consciously, for example, they are in a hurry, want to eat quickly and have made the decision to indulge. This provides a plausible explanation on the negative self-control coefficient. Still, impulsiveness turned out not to be significant in our research model. Further research is needed to investigate this interesting phenomenon in fast-food menus. Hypothesis

Table IV. Summary of hypotheses

H1. Higher levels of variety seeking are positively related to healthy food choice from a fast-food menu H2a. Higher levels of self-control positively relate to healthy food selection from a fast-food menu H2b. Lower levels of impulsiveness positively relate to healthy food selection from a fast-food menu H3. Higher levels of natural content in food positively relate to healthy food selection from a fast-food menu H4. Higher levels of dietary and weight control behaviours positively relate to healthy food selection from a fast-food menu H5. A healthy food-related lifestyle positively relates to healthy food selection from a fast-food menu H6a. Intention positively relates to healthy food selection from a fast-food menu H6b. Satisfaction positively relates to healthy food selection from a fast-food menu H7. A heart icon positively relates to healthy food selection from a fast-food menu H8. Available calorie and fat information positively relates to healthy food selection from a fast-food menu

Supported? Yes No No No Yes Yes No Yes Yes No

Our research also indicates content of food and diet and weight control should be treated as separate constructs rather than one. Participants who were more concerned about the content of food (i.e. natural vs artificial ingredients) were less likely to select healthy menu items than unhealthy ones. However, the p-value for this construct was equal to 0.049 and this construct was composed of only two items. Increasing the sample size and adding new survey items to the scale is appropriate for future research. Furthermore, participants who were more concerned about their diet and weight were more likely to select healthy than unhealthy food. Finally, the analysis of satisfaction and intention to dine provided us with interesting insights. Satisfaction with the FFR was found to have a positive influence on selecting a healthy meal over an unhealthy one – participants who were satisfied with our FFR menu were more likely to select healthy selections over unhealthy ones. This can mean that customers concerned about their health were satisfied that our FFR offered healthy meals, which might have exceeded their expectations regarding the food options. On the other hand, participants who demonstrated higher levels of intention to dine in on our FFR were less likely to order a healthy meal than to order an unhealthy one. Such customers may eat in FFRs on a regular basis, and may not be focused on food healthiness. The consumption at fast food is typically unhealthy is consistent with published research (French et al., 2001; Bowman et al., 2004). This study provides several implications for researchers. First, the data were collected for a relatively homogenous demographic group, college students. However, this group still represents an important population that dines at FFRs. The findings from the study should be used cautiously in attempting to generalize them to a broader population group. However, it may be appropriate to associate the findings to other users of FFR in a similar age group. Second, the conduct of a factor analysis is subject to professional judgements that have the potential to influence the results and outcome of any survey-based study. For example, we decided to retain items that loaded on the factors at ⱖ0.5. Had we instead used a 0.6 or 0.7 criteria, we would have removed more items from each construct. However, such judgements are most appropriate when guided by balancing theory and statistical methods. Hence, we wanted to retain as many items as we could justify on a theoretical basis, providing the reliability of the measures was retained. Our constructs all meet the reliability criteria, but, in addition, we examined several alternative approaches such as an Oblimin rotation vs an orthogonal rotation to confirm the robustness of the constructs and the associated items that were retained. The results of this study provide insights for literature body, the fast food industry and their consumers. Understanding which factors affect the consumer’s choices in FFR gives restaurants a way for better communication of healthier food options to consumers. Restaurants can use the results to make modifications to their menus to better accommodate consumers’ dietary constraints. For example, McDonalds emphasizing heart-healthy salads allow for a health-conscious consumer to patron at that restaurant. The findings show to policymakers and FFRs how to communicate healthier options to consumers in an effort to assist them with making healthier food choices that affect their health and weight control. Conclusion Our goal was to investigate whether heart icons can significantly influence selecting healthy food in FFRs and the results support this claim. We believe that consumers rely


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heavily on icons and health claims when they are examining a fast-food menu because they need to order their food quickly. The heart icon may provide fast and accurate information about the content of food presented in the menu. In conclusion, heart icons in fast-food environments lead to higher probability of ordering healthy food from the menu rather than ordering unhealthy choices.

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Further reading Hennig-Thurau, T. and Klee, A. (1997), “The impact of customer satisfaction and relationship quality on customer retention”, Psychology and Marketing, Vol. 14 No. 8, pp. 737-764. Nunnally, J.C. (1967), Psychometric Theory, McGraw-Hill, New York, NY. Steptoe, A., Wardle, J., Fuller, R., Holte, A., Justo, J., Sanderman, R. and Wichstrøm, L. (1997), “Leisure-time physical exercise: prevalence, attitudinal correlates, and behavioral correlates among young Europeans from 21 countries”, Preventive Medicine, Vol. 26 No. 6, pp. 845-854. About the authors Kittipong Boonme is a PhD candidate in the Information Technology and Decision Sciences Department at the University of North Texas, where he received his MBA in Strategic Management. He has 15 years of experience in the food service and hospitality industry. His major research interests include consumer decision-making, food and service quality and logistics and

supply chain. Kittipong Boonme is the corresponding author and can be contacted at: [email protected] Bartlomiej Hanus is a PhD candidate in the Information Technology and Decision Sciences Department at the University of North Texas, where he received his master’s of science degree in Information Technologies. His major research interests include information security, cloud computing and decision-making. Victor R. Prybutok is a Regents Professor of Decision Sciences in the Information Technology and Decision Sciences Department and Associate Dean of the Toulouse Graduate School at the University of North Texas. He received, from Drexel University, his BS with High Honors in 1974, an MS in Bio-Mathematics in 1976, an MS in Environmental Health in 1980 and a PhD in Environmental Analysis and Applied Statistics in 1984. Prybutok is an American Society for Quality-certified quality engineer, certified quality auditor, certified manager of quality/organizational excellence and an accredited professional statistician (PSTAT®) by the American Statistical Association. Prybutok has chaired 13 doctoral dissertations, served on dozens of other doctoral committees, authored over 130 journal articles, several book chapters and more than 120 conference presentations in environmental modelling, systems measurement, quality control, risk assessment and applied statistics. In addition to directing research teams at the University of North Texas, he worked with the research nursing department at Thomas Jefferson University, published models on leukaemia incidence risk and ozone alert prediction and has developed and published survey instruments that measure perceptions and behavioural intention. He is currently a member of the Texas Cardiovascular Disease and Stroke partnership. Daniel A. Peak is an Associate Professor in Information Technology in the Information Technology and Decision Sciences Department, College of Business at the University of North Texas. He received his PhD in 1994 from the University of North Texas with majors in Information Systems and Finance. Peak has more than 20 years of IT consulting and planning experience working for executives of Fortune 500 companies, and has won and directed numerous production projects and research grants. He is an editor of the Journal of IT Cases and Applications Research. He is a member of the Decision Science Institute and Association for Information Systems and has publications in Informing Science, Information and Management, Information Design Journal, Information Systems Management and others. Christopher Ryan is a Creative Director for the University of North Texas. He earned his MFA in Design Research in 2012 from the University of North Texas and an MA and a BA in Art and Technology from the University of Texas at Dallas. He specializes in graphic, print, Web and interactive design, but is also skilled in other aspects of emergent media, including podcasting, blogging and social media. He is interested at exploring the intersection between liberal arts and technology. Beyond academics, he is also experienced in contemporary communication design trends such as mobile design, game development, social networks and real-time media.

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