This study evaluated the consumers’ demands and points of improvement for restaurant meal replacement through importance–performance analysis by the restaurant meal replacement segment market using food involvement. The results were as follows. First, after segmenting the restaurant meal replacement market using food involvement, it was classified into three markets (multiple involvements, exploration-oriented, and product quality-oriented). Second, an analysis of the importance of restaurant meal replacement selection attributes revealed taste, sanitation, quality, freshness, price, saving time, texture, ingredients, preparation process, and quantity to be highly important. An analysis of the differences according to the market type revealed the multiple involvement type to be more important than other groups, considering the restaurant meal replacement selection attribute element. Third, an analysis of the importance-performance analysis of restaurant meal replacement selection attributes revealed that quantity and price as the selection attributes that needed to be improved first in all three markets. In addition, in the multiple involvement type, food additives appeared as a selection attribute requiring priority improvement, revealing the characteristics of a market that cares about diet and health.

Introduction Consumers throughout the world, including Asia, are showing increased concerns about food safety. Public policy, industry, and academic researchers are turning increased attention to the effects of food labeling requirements. General food labels provide information about serving size, servings per container, total calories per serving, calories from fat, and minimum daily nutritional value. Consumers must then use the food labeling information to make individual dietary choices. Thus it is appropriate for researchers to ask how consumers formulate product choices and evaluations according to food labeling information including calorie counts and standardized nutritional information (Ford et al. 1996; Keller et al. 1997; Roe, Levy, & Derby 1999). Long-term strategies are critically needed to find ways to protect public health and to assure food safety. Health practitioners and governmental regulators have increased their efforts to address the growing problem by sponsoring programs for food safety and by requiring nutritional labeling. In answer to the need for further research in food consumption behavior (RFC), this study was conducted to investigate how manufacturers might use consumers’ perceptions of risks and involvement for planning the most effective food labeling. Theoretical Framework To find ways to promote general and social marketing healthful consumer use of food labels (Lefebvre, 1988; McDermott, 2000), this study utilizes consumer segmentation techniques in which consumers are categorized according to psychological and demographic profiles (Slater, Kelly, & Thackeray, 2006). That is, they are segmented based on essential homogeneous responses (Forthofer, 2000; Kotler, 1971) and demographic characteristics, including age, gender, income and social class, although demographics may be less effective than psychological differences for predicting responses to health promotions (Lefebvre, 1988; Slater, 1991). The psychographics approach to consumer segmentation, derived from marketing techniques, selects variables that predict health behaviors; that is, consumers are segmented according to how they process communication channel properties and message features (Rimal & Adkins, 2003). By focusing on consumer segmentation we elucidate how consumers react to food labeling designed to promote health and food safety. Consumer segmentation should help us understand why consumers might reject risky unhealthful behaviors and adopt protective healthful behaviors (Slater, 2006). The risk perception attitude framework (Garretson & Burton, 2000; Rimal & Real 2003; Turner, Rimal, Morrison &, Kim, 2006) is a theoretical perspective for segmenting consumers based on their perceptions of risk and their beliefs about personal efficacy. According to the risk perception attitude framework, risk perceptions are usually insufficient to motivate behavior, but when high risk perceptions are coupled with strong efficacy beliefs, people are more motivated to engage in self-protective behaviors. Social cognitive theory and the extended parallel process model also support the importance of efficacy beliefs as moderating risk perception effects on self-protective behavior (Bandura 1986; Witte 1994). Using the risk perception attitude framework for purposes of this study, consumers are classified into four groups according to their risk perception and self-efficacy as indicated by their involvement in health concerns. 1) The "indifference" group comprises study participants who have low risk perceptions and low involvement; they believe they face few risks, lack control of their actions, and are thus not motivated to undertake protective behaviors. 2) The "responsive" group comprises study participants who have high risk perceptions and high involvement and thus are motivated to undertake extensive self-protective behaviors. 3) The "proactive" group comprises participants who have low risk perception but high involvement; they believe strongly in their personal abilities to take control, but perceive low risk and are thus not motivated to engage in self-protective behaviors. 4) The "avoidance" group comprises study participants who have high risk perceptions and low involvement; they are concerned about the need to counter risks but lack the self-efficacy and involvement to follow recommendations. Research Questions To examine the risk perception attitude framework in the context of research on food consumption behavior (RFC), three central research questions are posed: RQ1: How are consumers classified according to their level of perceived risk and involvement? RQ2: Do different consumer types show different attitudes toward paying higher prices for safer food and toward paying attention to food labels? RQ3: What factors influence consumer classifications? Methods Data for this study came from research on food consumption behavior (RFC) conducted by Korea Rural Economic Institute (KREI) in 2014. In 2013, the KREI began gathering data regarding food consumption behavior to help the food industry develop more efficient use of food resources. RFC data are appropriate because they include data about various consumption patterns regarding food lifestyles, purchases, and food safety. Specifically, RFC for this study, we gathered data for a stratified sampling of 6,311 consumers, 19 to 75-years-old, living in 16 metropolitan city-regions in South Korea. Table 1 shows general features of the research participants. Among the respondents, 44.2% were men; 55.8% were women; 10.7% were 19 to 25-years-old; 37.6% were high school graduates; 46.9% had lower than middle school graduation levels, 21.9% were college graduates, 2.3% had post-graduate levels, 1.1% were uneducated; 36.5% had average monthly family incomes of 200~399; 1.3% had the highest rate of 1000 and more; 1.0% had low to moderate interest in health; 42.8% reported that they bought food two or three times weekly; 0.7% reported buying food once a month. Respondents reported an average 3.93 regarding risk perceptions for food safety. Their reported average level of involvement was 3.32; average of intention to pay higher prices for safe food was 3.37, and their average likelihood of checking food labels was 3.15. Measurement To score education levels, the uneducated group = 1, less than middle school = 2, high school graduates = 3, college graduates = 4, and postgraduates = 5. A five-point Likert-type scale was used to measure participants’ interest in their health (1 = complete indifference to 5 = very much interested). Also a five-point Likert scale was used to measure perceived risk for twelve items related to food safety: foreign substances, pesticide residue, use of antibiotics in livestock and fish, natural toxicity, food additives, heavy metals, endocrine disruptors, bacterial contamination, livestock disease, GMO, irradiation, packing hazards, and allergens (1 = not concerned at all to 5 = very concerned). Involvement was measured for three questions regarding food origin, food materials, and eco-friendly products (1 = not concerned at all to 5 = very concerned). Intentions to pay higher prices for safe food and to check food labels were measured from 1 = not at all to 5 = very positive. Results Four consumer groups were classified according to their level of perceived risk and involvement. We followed previous RPA model studies (e.g., Sullivan et al., 2008; Jo & Yoo, 2011) and classified groups based on median perceived risk and involvement: (≥4.00) for high perceived risk, (<4.00) for low perceived risk, (≥3.333) for high involvement, and (< 3.33) for low involvement. The responsive group had high perceived risk and high involvement; the proactive group had low perceived risk and high involvement; the avoidance group had high perceived risk and low involvement; and the indifference group had low perceived risk and low involvement. Additionally, ANOVA with post-hoc Tukey test was conducted to examine the average difference among the four groups regarding their intentions to pay higher prices for safe food and to check food labels. Multinomial logit regression was performed to discover the factors that influence classification of consumer types. Classification of consumer types according to perceived risk and involvement Table 1 shows the consumer classifications according to the level of perceived risk and involvement: 1,198 participants, 21.8%, were in the indifference group with low perceived risk and low involvement; 1,254 participants, 22.8%, were in the proactive group with low perceived risk and high involvement; 1,125 participants, 20.5%, were in the avoidance group with high perceived risk and low involvement; 1,924 participants, 35.5%, were in the responsive group with high perceived risk and high involvement. Among the four groups, the responsive group had a statistically significant relatively high ratio: χ2 value for group classification was 79.695 (p <.001). Consumer classification differences in purchase intentions to pay higher prices for safe food and to check food labels Table 2 shows differences in intentions to pay higher prices for safe food and to check food labels. The proactive group showed the highest average intentions to pay higher prices for safe food at 3.52, followed by the responsive group at 3.51, the avoidance group at 3.25, and the indifference group at 3.16. The differences among the groups were statistically significant. A Tukey post-analysis showed that the high involvement group, in contrast with the low involvement group, showed higher average intentions to pay higher prices for safe food. Among the low involvement groups, those with high perceived risk had higher average intentions than those with low perceived risk. The responsive group showed the highest average intentions to check food labels at 3.44, followed by the proactive group at 3.43, the avoidance group at 2.74, and the indifference group at 2.27. The differences among the groups were statistically significant. A Tukey post-analysis showed that high involvement groups, in contrast with low involvement groups, showed higher average intentions to check food labels, but no difference was found according to the level of perceived risk. Influential factors of consumer segmentations Table 3 shows the results of examining the factors of gender, age, education, monthly average family income, and interest in health that are typical in consumer segments. Comparing all groups with the responsive group, the indifference group was most likely to comprise young women who had lower educational levels, lower monthly income, and less interest in health. The proactive group was most likely to be made up of men. The avoidance group was most likely to be made of young men who had lower educational levels, lower monthly incomes, and less interest in health. Discussion This study is an investigation of the theoretical framework of risk perception and involvement according to indifference, proactivity, responsiveness, or avoidance consumer segments. The study centrally indicates that the four risk perception–involvement framework groups differ in their perceptions of risk and the extent of their involvement. By revealing the importance of high involvement as a fruitful intervention strategy, the results suggest practical implications for public policymakers and marketers who strive to devise appropriate food labeling. Social cognitive theory has long stressed the importance of enhancing personal involvement (Bandura 1986). That insight can be applied to the risk perception attitude framework for identifying particular audiences who will respond to involvement-enhancing messages. Our findings suggest that a useful strategy in promoting change is to recognize that consumers will react differently according to their tendencies toward indifference, proactivity, responsiveness, or avoidance.

This study aimed to identify the effects of health-related menu choice attributes on customer behavioral intentions at wellbeing restaurants and analyze the moderating effects of food involvement and trust, which can influence customer preference and their intentions to visit well-being restaurants. This study designed a survey, and 351 respondents who have eaten at well-being restaurants completed the questionnaire. Exploratory factor analyses were conducted to identify underlying dimensions related to health-related menu choice attributes, food involvement, and customer behavioral intentions toward well-being restaurants. The three factors regarding health-related menu choice attributes and the three factors related to food involvement were identified. In order to test the relationships between health-related menu choice attributes and behavioral intentions as well as to investigate the moderating effects of food involvement and trust, hierarchical regression analyses were conducted. Results indicated that the three factors of health-related menu choice attributes were significantly and positively related to behavioral intentions. Among food involvement factors, dining environment and cooking were significantly related to behavioral intentions toward well-being restaurants. Trust had a significant influence on behavioral intentions. Results showed that food involvement and trust could moderate the effects of health-related menu choice attributes on behavioral intentions toward well-being restaurants.

An individual's food-related personal traits play an important role in influencing personal food choice and habits. According to culture, their influence can manifest differently. To ascertain personal traits about food, FNS (food neophobia scale) and FIS (food involvement scale) were employed in recent studies. This study aimed to understand the food culture and food choices of East-South Asians who live or stay in Korea through comparison of FNS and FIS. Eighty Koreans and 233 East-south Asians (Indonesians, Filipinos, Malaysians, Vietnamese, Thai, Singaporeans, and Bangladeshi) completed a questionnaire to measure FNS (10 questions), FIS (12 questions), and sociodemographic conditions (9 questions). ANOVA was conducted to ascertain FNS and FIS between the groups, and regression analysis was carried out to determine which sociodemographic factors had an effect. The items were analyzed to determine the differences according to gender, age, marital status, nationality, religion, occupation, educational background, monthly income, and length of residence in Korea. FNS showed significant differences between the groups with regard to sociodemographic characteristics, except gender, age, and marital status, whereas FIS showed significant differences in gender, nationality, religion, occupation, educational background, monthly income, and length of residence in Korea. The results of the regression analysis suggest that nationality strongly affected FNS and FIS, and FIS was also affected by gender.

The principal objective of this study was to assess the effects of food involvement moderating the relationship between food choice motives, including health concerns, weight control and ethical concern, and fruit consumption. A total of 290 questionnaires were completed. Moderated regression analysis was utilized to assess the relationships among variables. The results of the study showed that the results of data analysis also indicated good model fit. The direct effects of health concerns on fruit consumption were statistically significant in Models 1 and 2. However, the direct effects of ethical concern on fruit consumption were statistically significant in Model 3. As had been expected, the interaction of ethical concerns and food involvement exerted a significant effect on fruit consumption in Model 3. However, the interaction of health concern and food involvement, as well as weight control and food involvement exerted no significant effects on fruit consumption. Moreover, ethical concerns about fruit consumption exerted a significant negative effect at the low level and a positive effect at the high level of food involvement, except in cases in which the level of food involvement was medium. The results of this study revealed that fruit marketers should attach importance to the interaction effect of food involvement in order to better understand the elements of market demand and customer loyalty.

The purpose of this study was to measuring the causal relationships among food involvement, health, mood, convenience, sensory appeal, weight control and vegetable consumption. A total of 290 questionnaires were completed. Structural equation model was used to measure the causal relationships among constructs. Results of the study demonstrated that the structural analysis result for the data also indicated excellent model fit. The effects of food involvement on health, mood, convenience, sensory appeal, weight control and vegetable consumption were statistically significant. As expected, health, mood, sensory appeal and eight control had significant effects on vegetable consumption. Moreover, health, mood, convenience, sensory appeal and weight control played mediating roles in the relationship between food involvement and vegetable consumption. In conclusion, based on structural analysis, a model was proposed of interrelations among food involvement, health, mood, convenience, sensory appeal, weight control and vegetable consumption. It should be noted that the original vegetable consumption model was modified and should, preferably, be alidated in future research. Other variables, such as attitude, subjective norm and perceived behavior control, may be incorporated to form vegetable consumption models that consist of new antecedent and consequence pairs.

The objectives of the present study were to assess the preschool-children's awareness of nutrition, their level of control over foods and involvement in food-related activities and to examine the interrelationships among these variables. The children of this study demonstrated low levels of awareness of the concepts of food groups and the roles of both foods and exercise in energy balance. But the degree of children's awarences about the concepts of food transformations, food origins and food values was favorable. The range of possible scores was 0 to 18, while the range of the children's scores was 2 to 16. The mean score was 9.3, represently 52% of the questions answered correctly. Factors associated with the children's involvement in food-related activities were children's age, familly's income and mother's dietary balance. Children who were more involved in food related activities had significantly higher nutrition awareness scores.

음식은 세계인이 공유하는 공통의 언어이다. 최근 지구촌의 각 문화권이 보유하고 있는 독특한 음식문화의 가치는 관광을 통해 재발견되고 있다. 음식은 유.무형의 관광 상품과 서비스의 가장 중요한 요소이면서, 관광지의 이미지를 강화시킬 수 있는 핵심적인 요소이기 때문이다. 더 나아가 ‘음식’ 자체가 관광활동의 직접적인 동기가 되고 있고, 관광 활동의 한 부분을 차지하면서 문화, 역사, 관광지의 특성이 음식과 융화되어 특정지역이나 민족의 독특한 음식을 먹기 위한 미식관광(gastronomic tourism)이 점차 활성화되고 있다. 본 연구의 목적을 달성하기 위해 미식관광을 경험하거나 계획 중인 미식 관광객을 대상으로 설문조사를 하였으며, 총 300부의 연구 설문지 중 84부의 불성실한 답변 설문지를 제외한 216부의 설문지를 최종분석에 활용하였다. 분석에는 SPSS 23.0을 이용하여 신뢰도 분석, 요인분석, 상관관계 분석, 선형회귀분석을 하였으며 분석결과는 다음과 같다. 첫째, 미식관여도의 미식관광동기에 유의한 영향을 미치고 둘째, 미식관여도는 만족과 추천의도에 유의한 영향관계를 형성하였으며 셋째, 미식관광동기와 만족·추천의도 간에 유의한 영향관계를 형성하였다. 따라서 본 연구의 모든 가설은 채택되었고 미식관여도와 미식관광 속에서 미식의 중요성에 대한 관심과 방향성에 대한 실무적 시사점 또한 제공하였다.