How does the consumer choose a restaurant? An overview of the determinants of consumer satisfaction.

The failure rate of restaurants is high in many countries, primarily because of the complex relationships between services and customers. Therefore, improving restaurant customer experience is a significant challenge for entrepreneurs. This multi-dimensional experience encompasses several aspects that may or may not be related to food consumption. Many restaurant owners can avoid bankruptcy if they understand theories of service quality and the factors involved. The objective of this research is to identify and summarize known important factors that lead consumers to choose, patronize or be satisfied with a restaurant. The research question for this review is: What are the important factors that influence consumers (population) to choose, patronize, or be satisfied with a restaurant  (outcome)? Therefore, we conducted an integrative review to address this question. We included 111 studies and identified 117 factors/indicators related to consumer satisfaction and restaurant choices. First, we grouped these factors into four categories based on the Big Four restaurant attributes: atmosphere, food, service, and price & value. Four categories emerged based on consumer- and business-related aspects: behavioral intentions, values and beliefs, experiences, and companies. The "food" category is the most important factor in consumer choice and experience. However, the importance of this category may vary depending on the situation (e.g., lunch, dinner, weekends, weekdays) and should be carefully considered, as all categories were relevant but intricate. Such factors are associated with many positive outcomes, such as satisfaction, loyalty, brand love, patronization, and intent to visit and revisit.

Exploring dark kitchens in Brazilian urban centres: A study of delivery-only restaurants with food delivery apps.

Dark kitchen is a delivery-only restaurant that operates without direct contact with the consumer, has no premises for local consumption and sells exclusively through online platforms. The main objective of this work is to identify and characterise dark kitchens in three urban centres featured in the most used food delivery app in Brazil. To this end, data collection was conducted in two phases. In the first phase, through data mining, we collected information from restaurants in three cities (Limeira, Campinas and São Paulo - Brazil) that were provided in the food delivery app. A total of 22,520 establishments were searched from the central point of each of the cities. In the second phase, the first 1,000 restaurants in each city were classified as dark kitchens, standard, or undefined restaurants. A thematic content analysis was conducted to further distinguish the dark kitchen models. Of the restaurants evaluated, 1,749 (65.2%) were classified as standard restaurants, 727 (27.1%) as dark kitchens, and 206 (7.7%) as undefined. In terms of the characteristics of dark kitchens, they were more dispersed and located further away from the central points compared to standard restaurants. Meals in dark kitchens were cheaper than in standard restaurants, and had a lower number of user reviews. Most of the dark kitchens in São Paulo served Brazilian dishes, while in the smaller cities, Limeira and Campinas, it was mainly snacks and desserts. Six different models of dark kitchen were identified: Independent dark kitchen; shell-type (hub); franchise; virtual kitchen in a standard restaurant (different menu); virtual kitchen in a standard restaurant (similar menu but different name); and home-based dark kitchen. The modelling approach and methodology used to classify and identify dark kitchens is considered a contribution to science as it allows a better understanding of this fast growing sector of the food industry. This in turn can help to develop management strategies and policies for the sector. Our study is also of value to regulators to determine their proliferation through urban planning and to promote appropriate guidelines for dark kitchens as they differ from standard restaurants.

What is a dark kitchen? A study of consumer's perceptions of deliver-only restaurants using food delivery apps in Brazil.

Dark kitchens are restaurants with no storefronts, no direct customer interaction and delivery-only commercial kitchens that rent out shared or private kitchen spaces to food businesses. The objective of this study is to determine consumers' knowledge about dark kitchens and the factors that influence willingness to pay and intention to purchase meals in this restaurant model. It were surveyed 623 Brazilian consumers. First, consumers' knowledge of the term dark kitchen was determined using specific questions. Then, consumers were presented with the actual meaning of dark kitchens and were asked about their intention to use this restaurant model. To this end, participants were presented with 25 indicators to assess the following constructs: willingness to pay and purchase intention, trust in health authorities, trust in food delivery app, perceived food safety, quality control, consumer experience, and solidarity with the foodservice sector. Overall, 73.4 % of participants reported having heard of the term dark kitchen. Using a descending hierarchical classification, four classes of definitions were found. The factor solidarity with the foodservice sector (ß = 0.440; p < 0.001) had the greatest positive influence on willingness to pay and purchase intention, followed by perceived food safety (ß = 0.273; p < 0.001); quality control (ß = 0.125; p = 0.003); consumer experience (ß = 0.110; p = 0.002) and trust in health authorities (ß = 0.059; p = 0.047). Even if consumers cannot accurately describe what a dark kitchen is, there is a positive intention to purchase food produced in this kitchen model. It is important to develop strategies to promote and improve dark kitchen models. Finally, it is suggested that health authorities and app operators pay more attention to improving food safety in these establishments, as consumers have low risk perception about them.

What Motivates Consumer Food Safety Perceptions and Beliefs? A Scoping Review in BRICS Countries.

This scoping review aimed to map the main evidence in the existing literature regarding consumer perceptions and beliefs regarding food safety in the context of BRICS (Brazil, Russia, India, China, and South Africa) countries. Articles were searched in the Web of Science, Scopus, and SciELO databases. The last search was performed on November 2021. Only the studies conducted within BRICS countries were included. The synthesis aimed to group similarities in consumer beliefs and perceptions of food safety. After screening, 74 eligible articles were included in the study. Of the 74 studies analyzed, 49 (66.2%) were carried out in China, 14 (18.9%) in Brazil, 5 (6.8%) in India,4 (5.4%) in South Africa, and 2 (2.7%) in Russia. Thirty-three motivators of perceptions and beliefs regarding food safety were identified. Food safety motivators were grouped into three categories: (1) sociodemographic characteristics, (2) cognitive aspects, and (3) other. In the "sociodemographic characteristics" category, the motivator with the highest number of corresponding results was education level (results = 22), followed by income (results = 22), both positive drivers for food safety perceptions. The "cognitive aspects" category comprised the majority of the identified motivators. Concern for food safety (results = 32) and risk perception (results = 30) were the motivators with the highest number of results among all categories and motivators. Finally, the main motivator in the "other" category was place of consumption/purchase (results = 8), focusing on consumers underestimating the risk of having a foodborne disease when eating away from home. China and Brazil are leading the way in studies on this topic. Consumers' perceptions are influenced by socioeconomic characteristics (e.g., age, gender, education level, income), cognitive aspects (e.g., knowledge, risk perception, food concerns, previous experience with food safety incidents) and other situational factors (e.g., price, place of purchase, traceability).

The use of food delivery apps during the COVID-19 pandemic in Brazil: The role of solidarity, perceived risk, and regional aspects.

This study aimed to evaluate the use of food delivery apps (FDA) during the COVID-19 pandemic in Brazil. A total of 950 questionnaires were collected, covering four Brazilian regions: Southeast, Central-West, Northeast, and South. The data was collected during the peak of the second wave of the pandemic. A questionnaire with 39 measurement items was applied using an online survey. These items were evaluated using a five-point Likert scale covering the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2). The data was analyzed using covariance-based structural equation modeling. About 47% of consumers use FDA weekly. The continuance intention of FDA during the pandemic in Brazil was affected by performance expectancy (ß = 0.496; p < 0.001), social influence (ß = 0.094; p < 0.001), hedonic motivation (ß = 0.068; p = 0.026), price value (ß = 0.103; p < 0.001), habit (ß = 0.305; p < 0.001), frequency of using FDA (ß = 0.051; p = 0.039), and solidarity with the foodservice sector (ß = 0.090; p < 0.001). It was also observed that the continuance intention reduces risk perception (ß = -0.403; p < 0.001), and risk perception reduces the frequency of using FDA (ß = -0.178; p < 0.001). The results indicate that the UTAUT2 strongly explains consumers' continuance intention. Differences in path estimates among Brazilian regions were observed, indicating some regional differences. It was possible to observe a tendency of using FDA during and after the pandemic, motivated by several factors. The FDA developers and foodservice managers could use this data to improve their services. Policies must be established to increase consumer and employee safety during the delivery service.

Should I stay, or should I go? Consumers' perceived risk and intention to visit restaurants during the COVID-19 pandemic in Brazil.

This study aimed to verify how consumers' intention to visit restaurants during the pandemic is affected by consumers' risk perception and different types of trust. The sample was composed of 546 consumers from 89 different cities in Brazil. An adapted 43 items questionnaire with 5-point scales was administered, and analyzed usingstructural equation modeling. The results indicate that consumers' trust in a restaurant and brand, fair price, solidarity with the restaurant sector, disease denial, and health surveillance trust predict intention to visit a restaurant during the COVID-19 pandemic. Age has significant moderated effects, reducing disease denial effects. The trust in restaurants and brands was the factor with the largest effect size. In a multigroup analysis, it was found that solidarity with the sector does not affect the intention to visit restaurants for consumers without formal work. It is discussed the implications of an increased consumers' risk perception, directly affecting their intentions. Special attention to consumers' trust and fair price perception is fundamental, given consumers' solidary inclination toward helping the restaurant sector. These aspects must be recognized by restaurant owners and managers to be improved and be used to attract consumers.

The mandatory labeling of genetically modified foods in Brazil: Consumer's knowledge, trust, and risk perception.

Since 2003, Brazilian-specific legislation has stipulated that foods containing more than 1% of genetically modified (GM) ingredients must provide information regarding their origin with an identification symbol on its label. The purpose of this study was to verify the knowledge of consumers concerning the mandatory labeling of foods containing genetically modified ingredients and analyze the possible motivations behind the willingness of the consumer to buy these foods in Brazil. Research was conducted on 224 consumers of different socioeconomic levels from Limeira, São Paulo (SP), Brazil. Consumers were asked about socio-demographic variables and were assessed for their knowledge of the symbol for genetically modified ingredients on food labels. Depending on the consumers' answer about the symbol, they would be directed to a specific set of assertions. In the end, seventeen assertions were scored using a 5-point Likert scale to determine their profile. These assertions were categorized into five constructs: social trust, reduced price, perceived risk, perceived quality, and willingness to buy. This data was analyzed using Structural Equation Modelling. Most consumers (74.6%) did not recognize the symbol used in the mandatory labeling, although a younger age, a concern regarding GM foods, and a high level of education increased the chances of recognizing the symbol. Many of the consumers who were able to identify the symbol have found the GM labeling difficult to interpret. With regard to their willingness to buy GM foods, positive effects were observed for reduced price and perceived quality, while a negative effect was observed for risk perception. The effect of risk perception was moderated by social trust and perceived quality. These results indicate that although the Brazilian GM food label policy is aligned with similar policies in developed countries, it has been implemented without an adequate disclosure. The consumers had a high confidence with regards to the science and the government, reducing their risk perception. Our findings indicate that in order to improve the effectiveness of this food policy, the Brazilian Ministry of Health should invest in advertising the labels, targeting the elderly and individuals with lower levels of education.