e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 457 Alcinei Cautela Junior Universidade Anhembi Morumbi Aline de Godoy Moreira Universidade Anhembi Morumbi Claudio Gonsalves de Souza Universidade Anhembi Morumbi Paulo Sergio Gonçalves de Oliveira Universidade Anhembi Morumbi Sérgio Luis Ignácio de Oliveira Universidade Anhembi Morumbi Buying Decision: The Choice of Restaurants to Have Dinner The aim of this paper is to investigate consumers buying process and selection of a restaurant for dining. The study employs a questionnaire, and the number of respondents was 383 people. The Engel-Blackwell-Miniard (2005) model was used to create a conceptual research framework to guide the analysis of consumers' behavior when choosing restaurants to have dinner, and how consumers identify a need, search for information, analyze these decisions, buy and behave after the purchase process. The results suggest that consumers' choices follow a linear method when they decide about a restaurant which they will have dinner, which confirms the Engel-Blackwell-Miniard (2005) models. Based on the findings, practical implications are proposed. Key words: Food and beverage sector, Marketing, Consumer behavior, Buying decision process, Spearman’s Rho Alciney Cautela Júnior Universidade Anhembi Morumbi, Professional Master in Food and Beverage Management Post-graduate Student, Faculty of Tourism and Hospitality R. Casa do Ator, 275 - Vila Olímpia, São Paulo - SP, 04546-001 Brazil Phone: [055] (011) 4007-1192 Email: aljunior@anhembi.br Aline de Godoy Moreira Universidade Anhembi Morumbi Professional Master in Food and Beverage Management Post-graduate Student, Faculty of Tourism and Hospitality R. Casa do Ator, 275 - Vila Olímpia, São Paulo - SP, 04546-001 Brazil Phone: [055] (011) 4007-1192 Email: aline.godoy@hotmail.com http://ertr.tamu.edu/ mailto:aljunior@anhembi.br mailto:aline.godoy@hotmail.com e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 458 Claudio Gonsalves de Souza Universidade Anhembi Morumbi Professional Master in Food and Beverage Management Post-graduate Student, Faculty of Tourism and Hospitality R. Casa do Ator, 275 - Vila Olímpia, São Paulo - SP, 04546-001 Brazil Phone: [055] (011) 4007-1192 Email: claudio.gonsalves@gmail.com Paulo Sergio Gonçalves de Oliveira Universidade Anhembi Morumbi Professional Master in Food and Beverage Management Post-graduate Professor, Faculty of Tourism and Hospitality R. Casa do Ator, 275 - Vila Olímpia, São Paulo - SP, 04546-001 Brazil Phone: [055] (011) 4007-1192 Email: psoliveira@anhembi.br Sérgio Luis Ignácio de Oliveira Universidade Anhembi Morumbi Professional Master in Food and Beverage Management Post-graduate Professor, Faculty of Tourism and Hospitality R. Casa do Ator, 275 - Vila Olímpia, São Paulo - SP, 04546-001 Brazil Phone: [055] (011) 4007-1192 Email: slmarketing@uol.com.br Alciney Cautela Júnior is Professional Master in Food Beverage Student, MBA Coordinator and Graduation Professor at Universidade Anhembi Morumbi and FMU. His current research’s focuses on ethnic Restaurants Consumers Behavior. Aline de Godoy Moreira is Professional Master in Food Beverage Student at Universidade Anhembi Morumbi and Restaurant’s Consultant. Her current research’s focuses on Restaurant Indicators analyses. Claudio Gonsalves de Souza is Professional Master in Food Beverage Student at Universidade Anhembi Morumbi and Under graduation Professor at Universidade Anhembi Morumbi. His current research’s focuses on Information Technology applied for Restaurants. Paulo Sergio Gonçalves de Oliveira is Post Graduation Professor at Professional Master in Universidade Anhembi Morumbi. His current research’s focuses on Structural Modeling http://ertr.tamu.edu/ mailto:claudio.gonsalves@gmail.com mailto:psoliveira@anhembi.br e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 459 Analyses, Multicriteria Analyses and Descriptive Statistics applied for Food and Beverage Management. Sérgio Luis Ignácio de Oliveira is Post Graduation Professor at Professional Master in Universidade Anhembi Morumbi. His current research’s focuses on Marketing, Consumer Behavior, Marketing History, Neuromarketing and Structural Modeling Analyses applied for Food and Beverage Management. http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 460 Introduction The food industry is an important part of the hospitality sector and is important to Brazilian society. Food Service is a growing market, which involves industrials clients and consumers, as well as a rising number of establishments. However, in spite of its growth and importance in the market, the sector presents some problems that require proper business planning to survive. According to the Industry Portal (Portal da Indústria, 2017), the food and beverage sectors represent approximately 20% of the processing industry's workers in Brazil and correspond to 10% of the total GDP, with a sales revenue higher than BRL 480 billion in 2012. Bars and restaurants, according to the Brazilian Association of Bars and Restaurants (Abrasel, 2017), represent approximately 2.4% of the Brazilian GDP. The Brazilian Micro and Small Enterprises' Support Service (Sebrae, 2017) highlights that the food sector employs 13% of the formal workforce in Brazil. According to the portal 'Food outside the home' (Alimentação fora do lar, 2017), the growth in the rate of food prepared outside the home increased, on average, 12% in this period. Consistent with the latest family budget research (POF) carried out by the Brazilian Institute of Geography and Statistics (IBGE), over 1/4 of the meals are taken outside the home in Brazil; in the big city centers, this ratio exceeds 1/3. Recent studies made by Forbes Magazine (2017) stress that, in Brazil, the meals taken outside the home represented 33% of the costs with food and beverage in 2014, and forecast that nearly BRL 300 billion will be spent by the end of 2015. In accordance with the Brazilian Association of Food Industries (ABIA), the businesses related to meals taken outside the home have been one of the main beneficiaries of http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 461 the consumption expansion in the last years, considering a sales revenue of BRL 38.6 billion in 2005, and an approximate value of BRL 140 billion in 2014 (ABIA, 2017). The purpose of this study is to understand the impact of the stages of the buying decision process on the choice of restaurants to have dinner. Only this specific meal was chosen to be analyzed due to the fact that the lunch and dinner decision-making processes are, in general, pretty distinct. In a subjective way, it can be observed that the choice of restaurants to have lunch is normally focused on basic food needs. The choice of restaurants to have dinner is usually different because people can go to have this meal for leisure, business or other special purposes. In his studies, Krause (2014) highlights the differences between diurnal and nocturne meals. To the author, the diurnal meals are typically taken in order to meet physiological needs. Therefore, the technical and objective aspects, such as the quality of the food, are more important (Chen, Raab, & Chen, 2017). On the other hand, in a nocturne meal, since it is commonly related to leisure, the subjective aspects of a gastronomic experience, such as a good company, are more relevant. Theoretical Reference Consumer Behavior In markets increasingly more complex and competitive, thinking in terms of Marketing (that is, according to the current concept that alleges that Marketing consists of actions organized with the purposed of satisfying the consumers’ needs and wishes) is a matter of survival for the companies. As stressed by Cobra (2011), Kotler & Keller (2006), Reade et al. (2015) and Oliveira (2007), the companies have to ensure sustainable competitive differentiating factors and need to be perennial, besides having a corporate thought and a philosophy that lies in thinking in terms of marketing when interacting with the market and with the stakeholders. http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 462 Therefore, in order that the organizations manage to fulfill the clients' needs and wishes, it is important to understand the consumers' purchase behavior, which consists of studying how the individuals, groups and organizations select, buy, use and discard goods, services, ideas or experiences so that their needs and wishes can be addressed (Kotler & Keller, 2006; Bolton, Lemon, & Verhoef, 2004; Pankajakshi & Savitha, 2015). Gade (1998) highlights that studying the consumer's behavior comprises the physical, mental, and emotional activities are done when selecting, buying, and using products and services to meet their needs and wishes. However, Bauer et al. (2013) call attention to the fact that enterprises prioritize the investment in customer management they had only little know about customer management decisions which explain the importance of researchers develops researches in this aspect. Complementing the concepts presented, the consumer’s behavior (Rosa, Sillani, & Vasciaveo, 2017) may also be seen as the ways of understanding how the clients chose, buy, use and discard the products offered by the organizations, as well as the which are the main factors influencing the consumer in this decision-making process and all the agents involved, as claimed by Cobra (2011), Blackwell et al. (2005), Limeira (2008), Oliveira (2007), Reade et al. (2015), Samara & Morsch (2004), Sheth, Mittal & Newman (1998) and Solomon (2003). Karslakian (2000) stresses that the consumer’s behavior is an applied science arising from the human and social sciences (especially economics, psychology, sociology and even anthropology), the purpose of which is to figure out the consumption behaviors by adopting a multidisciplinary perspective. Mowen (1988), in turn, emphasizes that the consumer's behavior is the systematic study of the purchase and exchange processes involved in the acquisition, consumption, http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 463 assessment, and discard of products, services, ideas, and experiences. The American Marketing Association (AMA) defines it as: "The dynamic interaction of effect and cognition, behavior, and the environment by which human beings conduct the exchange aspects of their lives. 2. The overt actions of consumers. 3. (consumer behavior definition) The behavior of the consumer or decision maker in the market place of products and services. It often is used to describe the interdisciplinary field of scientific study that attempts to understand and describe such behavior". Besides understanding the importance of studying the consumer's behavior, which we can extract from the concepts presented, another process required to achieve the primary purpose of marketing (satisfying the consumers' needs and wishes) is realizing the buying process phases (Lu & Gursoy, 2017). The model by Engel, Blackwell and Miniard (2005) will be adopted for this particular study, since it is one of the most commonly used in the marketing literature, having already been analyzed in several occasions, such as in the seminal papers by Bettman (1998), Bhalerao, Pandey & Kumar (2017), Erasmus, Boshoff & Rousseau (2001), Farley & Ring (1970), Goldstein & Almeida (2000), Hunt & Pappas (1972), Kollat, Engel & Blackwell (1970), Lopes & Silva(2012), Mowen (1988), Nalini, Cardoso & Cunha (2013), and Richers (1984). According to this model, the consumers go through the following phases when buying a product or service: Problem Identification, Search for Information, Alternatives Analysis, Buying Decision, and Post-Purchase Behavior. This model is renowned in the marketing literature, as noticed in the seminal works by Cobra (2011), Churchill & Peter (2003), Blackwell, Miniard & Engel (2005), Jisana (2014), Karslakian (2000), Kotler & http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 464 Keller (2006), Limeira (2008), Longart, Wickens & Bakir (2016), Mowen (1988), Reade et al. (2015), Oliveira (2007), Samara & Morsch (2004) and Solomon (2003). The entire buying process, regardless of the involvement existing between the company and its consumers (since there are situations in the market in which the consumers have a high or a low involvement with the company and, consequently, with the product under the commercial process), undergoes the phases described in the model presented. Each of the phases must be systematically studied so that they can be converted into substantial sales to the company, and into valuable deliveries to the consumers, aiming to address the needs and wishes of the company's target clients. For Blackwell, Miniard & Engel (2005), Gade (1998), Garcia, Moreira, Lima & Galli (2017), Hettiarachchi, ,Wickramasinghe, Ranathunga,(2017), Pankajakshi & Savitha, 2015; Oliveira (2007), Richers (1984), Reade et al. (2015), Samara & Morsch (2004), Sheth et al. (1998) and Solomon (2003), this buying process starts with the Problem Identification (PI). It is the moment when the consumers realize they have an unmet need. This unmet need can be understood as an unbalance between a real condition (the consumers' current situation) and the desired condition (the situation in which the consumers want to be). This state is sufficient to make them act, in behavioral terms, so that the problem identified is solved. This problem identification phase may be driven by internal or external stimuli. Internal stimuli are those arising from the consumers’ inherent needs, such as the basic needs identified by Maslow to understand this unbalance situation. The external stimuli, on the other hand, are the Marketing strategies used by the companies, or other stimuli present in the environment that have the power of triggering the consumers’ latent needs (Blackwell et al., 2005; Cobra, 2011; Gade, 1998; Karsaklian, 2000; Kotler & Keller, 2006; Limeira, 2008; Mowen, 1988; Oliveira, 2007; Reade et al., 2015; Samara & Morsch, 2004; Sheth et al., 1998; Solomon, 2003). http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 465 After verifying the need, or a problem identified by the consumers, there is the Search for Information (SI) phase, which consists of researching products or services that may resolve the punctual problem. It is the moment when the consumers look for data that help them make a wise decision (Blackwell et al., 2005; Cobra, 2011; Gade, 1998; Jisana, 2014; Karsaklian, 2000; Kotler & Keller, 2006; Longart, Wickens & Bakir, 2016;Limeira, 2008; Mowen, 1988; Pankajakshi & Savitha, 2015; Oliveira, 2007; Reade et al., 2015; Samara & Morsch, 2004; Sheth et al., 1998). In this phase, the consumer resorts to Internal and External information. Internal Information consists of the consumers’ memories or experiences related to the problem identified. External Information is the data obtained from the relationship between the consumers and their external environment, such as: Personal Sources – when the consumers seek information before people with whom they have a direct contact –; Commercial Sources – advertising actions the companies perform in all consumer-relationship platforms –; Public Sources – sources related to media through which the consumers seek information, but there is no sponsor identified. In the marketing literature, it is known as Publicity –; and Experimental Sources – when the consumer literally experiments a product, such as a test- drive or a free sample (Gade, 1998; Kotler & Keller, 2006; Oliveira, 2007; Reade et al., 2015; Samara & Morsch, 2004; Sheth et al., 1998). This process serves to help the consumers making their decisions. These sources are used by the consumers to choose among the existing alternatives. Since there is a theoretical dependence between the “Problem Identification (PI)” and the “Search for Information (SI)”, the hypothesis H1 is that there is a relation between these two stages. Based on the information collected in the previous phase, the consumers move forward to the Alternatives Analysis (AA) process. It is the understanding that the http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 466 consumers make decisions based on the competitors and offers available, according to their financial restrictions, to the groups with which they interact, to their beliefs and to the value perception, that is, depending on variables that have an influence on the consumers’ behavior, such as the traditional Cultural, Social, Personal and Psychological factors (Cobra, 2011; Gade, 1998; Jisana, 2014; Kotler & Keller, 2006; Longart, Wickens & Bakir, 2016; Pankajakshi & Savitha, 2015; Oliveira, 2007; Reade et al., 2015; Samara & Morsch, 2004; Sheth et al., 1998). All these elements are being fed when constructing the buying decision process, in which the data are weighted and assessed having as basis the way how the consumer receives this information (Karsaklian, 2000; Limeira, 2008). For Kotler & Keller (2006) and Blackwell, Miniard & Engel (2005), there is a value judgment based on the functional features, on the emotional satisfaction, and on the benefit of using or possessing. Solomon (2003) adds the brand and the country of origin too. Because of this, the aspect the enterprises needs to acquire competence in satisfying customer needs providing information for decision process aiming to improve the enterprise's quick responses to achieve sustained success (Jayachandran, Hewett, & Kaufman, 2004). Since there is a theoretical dependence between the “Search for Information (SI)” and the “Alternatives Analysis (AA)”, the hypothesis H2 is that there is a correlation between these two processes. Afterward, we have the Buying Decision (BD) in the model proposed. That is the moment in which the consumer makes the purchase, after going through the previous phases (Jisana, 2014;Karsaklian, 2000; Longart, Wickens & Bakir, 2016; Pankajakshi & Savitha, 2015; Reade et al., 2015; Richers, 1984; Samara & Morsch, 2004; Sheth et al., 1998). In the Alternatives Analysis stage, the consumer creates preferences among the brands in the range of choices, besides creating an intention to buy the preferred brands. When forming this http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 467 purchase intersection, the client may undergo five subdivisions: decision for the brand, decision for reseller, decision for quantity, decision for occasion and decision for payment method (Kotler & Keller, 2006). In addition, it can be affirmed that, in the buying decision process, three factors have an influence on the consumers’ perception and will affect their decision: Attitude of the Others – the consumers consider the opinion of their peers regarding the posterior use of the product; Unforeseen Situational Factors – possible problems that may appear after the product purchase, such as a difficulty to pay in case something occurs with the product. This normally occurs when the value involved in the process is high; and Perceived Risk – the risks that may be involved in the purchase process, such as the consumer’s physical integrity, the product’s functionality, among others (Blackwell et al., 2005; Cobra, 2011; Gade, 1998; Limeira, 2008; Oliveira, 2007; Solomon, 2003). Since the Alternatives Analysis influences the Buying Decision, and since it is a previous and dependent stage when it comes to the consumers' decision-making, the hypothesis H3 is: there is a correlation between the "Alternatives Analysis (AA)" and the "Buying Decision (BD)". Finally, we have the Post-Purchase Behavior (PPB) in the model proposed. Although this is the final stage, it is also important, since the purpose of all organizations is to retain loyal consumers, who will keep buying, make positive comments concerning the organization and suggest the products to their peers. Therefore, the Post-Purchase Satisfaction – derived from the proximity between the clients’ expectations and the performance they notice –; and the Post-Purchase Actions – buying again or not – must be analyzed. Satisfied clients buy again, which does not happen to the consumers who were dissatisfied; Post-Purchase use and discord – among the ways to understand the consumers' satisfaction after they make a purchase, it can be inferred that the faster is the product use, the http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 468 greater the possibility that the consumers were satisfied with the purchase and, consequently, buy again (Blackwell et al., 2005; Cobra, 2011; Gade, 1998; Jisana, 2014; Limeira, 2008; Longart, Wickens & Bakir, 2016; Pankajakshi & Savitha, 2015; Oliveira, 2007; Solomon, 2003). Due to the theory presented and to the fact that there is a clear theoretical correlation between the preceding stages, the hypothesis H4 is that the "Buying Decision (BD)" process influences the "Post-Purchase Behavior (PPB)" process. Having the model presented above as a basis, the purpose of this paper is to understand the stages of the buying decision process when choosing restaurants to have dinner (Khalilzadeh, Ghahramani, & Tabari, 2017). The theoretical model, as well as the hypotheses, are shown in Figure 1: Figure 1 – Theoretical Buying Decision Model Source: Elaborated by the Authors http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 469 Materials and Methods The research conducted was characterized as empirical with a quantitative approach. As to the research procedures, the bibliographic and field analysis methods have been used by the researchers. For the field analysis, a questionnaire based on the Likert scale has been prepared to be replied to through the researchers’ social network (Gil, 2010). The data were collected employing the application of the questionnaire sent through the researchers' social network and personal email. This questionnaire had twenty-seven objective questions based on the Likert scale, and it was subdivided into six stages to identify the respondents' profile and analyze the five stages of the buying decision process (Gil, 2010; Malhotra, 2007). The questionnaire, designed in the Google Drive platform, was made available by email from November 21, 2016 to December 7, 2016. Then, the data were synthesized by criteria and organized in graphs and tables, enabling a broad, quantified, and summarized view, facilitating the data analysis. The questionnaire had thirty-five questions, subdivided into six parts. The first part sought to understand the respondents’ socio-demographic profile. In parts 2 to 6, the buying decision processes were measured, namely: Problem Identification; Search for Information; Alternatives Analysis; Buying Decision and Post-Purchase Behavior. Measurement scales used 5-point Likert scales to measure the level of agreement among the people who had completed the questionnaires. Since the questionnaire has been designed using the Likert scale, it adopts the Spearman’s Rho correlation coefficient (Pestana & Gageiro, 2013). The Spearman’s Rho coefficient ranges from -1 to 1. The closer it is to these extremities, the greater will be the linear association between the variables. The negative sign denotes that the greater is the range in a variable, the lower will be the value found in the other correlated variable (Pestana & Gageiro, 2013). http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 470 To calculate the sample was used the Levine, Berenson & Stephan (2000) formula for an undefined population with 90% of reliability and 5% of maximum error estimative. The formula was presented in figure 2: Figure 2 – Sample Estimation Formula Source: Levine, Berenson & Stephan (2000) Critical Value (Zα/2) = 0,10 = 1,645 E2 = 0,052 n = Estimated Sample Sample Estimation n = (1,6452 * 0,25)/0,052 => 270,6 = 271 The outcome demonstrated that’s the estimated sample for this study was 271 respondents which evidence the 314 collected data was enough for this analysis according to Levine, Berenson & Stephan (2000) recommendation for an undefined population with 90% of reliability and 5% of maximum error estimative. Results Analysis The non-probabilistic method of “sampling for convenience” has been adopted to choose the interviewees. As stressed by AAKER et al. (2012), this procedure is adequate for studies such as the one we have developed, but with the due reservation that its results do not allow a statistical generalization for the population. According to Table 1, the sample of 355 respondents was constituted in an almost unbiased way as to the gender, since 56% were women, and 44% were men. The majority of http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 471 the respondents (63%) were from 30 to 49 years old, whereas only 1% of them were 18 years old or less, and 3% were 60 years old or more. Data on the interviewees’ economic profile have also been collected using the social class criterion, based on the minimum salary (MS) ranges of IBGE. The sample was divided as follows: 4% earned up to 2 MS; 18%, from 2 to 4 MS; 47%, from 4 to 10 MS; 23%, from 10 to 20 MS; and 8%, more than 20 MS. Table 1 – Socio-Demographic Profile of the Respondents Gender Educational Status Female 56% Complete Basic Education 1% Male 44% Complete High School 2% Complete Undergraduate Education 40% Age Incomplete Undergraduate Education 16% Up to 18 years old 1% Complete Graduate Education 36% From 19 to 29 years old 21% Incomplete Graduate Education 6% From 30 to 39 years old 36% From 40 to 49 years old 27% Family Income From 50 to 59 years old 12% Up to 2 minimum salaries 4% From 60 years old on 3% From 2 to 4 minimum salaries 18% From 4 to 10 minimum salaries 47% Marital Status From 10 to 20 minimum salaries 23% Married 53% More than 20 minimum 8% http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 472 salaries Divorced 6% Unmarried 40% Widowed 1% Source: Elaborated by the authors The respondents have also been asked the frequency with which they go out to have dinner in restaurants. The answer to 76% of them was affirmative. The frequency volume in restaurants is shown in Figure 3. Figure 3 – Frequency with which they go out for dinner. Source: Elaborated by the authors The instrument of the collection was a structured questionnaire containing twenty- seven questions, divided into five stages. Besides the five steps, a sixth part collected http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 473 information about the demographic profile: gender and age, and information required to access the socio-economic profile. The sections were divided as follows: The first stage was constituted of five statements related to the first phase of the buying decision process when it comes to having dinner in restaurants – the Problem Identification. This stage starts when the buyers identify a problem or need. When receiving stimuli from the market or the internal needs, they notice that there is a difference between the real situation and the desired situation. The need may be driven by internal or external stimuli. It is the first step of the buying decision process, as affirmed by Blackwell, Miniard & Engel (2005), Gade (1998), Garcia, Moreira, Lima & Galli (2017), Hettiarachchi, ,Wickramasinghe, Ranathunga,(2017), Pankajakshi & Savitha, 2015; Oliveira (2007), Richers (1984), Reade et al. (2015), Samara & Morsch (2004), Sheth et al. (1998) and Solomon (2003). The second stage was constituted of six statements related to the Search for Information phase of the buying decision process when it comes to having dinner in restaurants. Regarding this issue, Kotler (1998, p. 180) emphasizes that the marketing professionals are quite interested in getting to know the main sources of information to which the consumer will resort, and the relative influence each one of these sources will have on the subsequent buying decision. They may even be interested in being aware of the moment when the consumer looks for internal or external information to resolve a punctual problem (2007). In a study on the Search for Information relating to wines, it was identified that there is a difference in the way how people go through this process depending on their gender. For instance, women prefer looking for information when buying this product, while men prefer doing so before going to the store (Farías & Fistrovic, 2016). http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 474 In such point, the customers’ educational level and their capacity of assessing the information have an important role and may have an impactful influence on the decision- making process (Bispo, 2017; Guerrero & Monroy, 2015; Romero-Martínez, Montoro- Sánchez, & Garavito-Hernández, 2017). It is also in this moment that the Search for Information process occurs, many times using informal processes, such as the word-of-mouth Search for Information, which consists basically of consulting the experience other consumers had about establishments or products (Inocêncio & Marques, 2016). The third stage was constituted of six statements related to the Alternatives Analysis phase of the buying decision process when it comes to having dinner in restaurants. Kotler (1998) highlights that there are several decision assessment processes, being the majority of the models cognitively oriented, that is, the consumers form opinions on the products rationally and consciously. Reade et al. (2015) stress that it is the moment when the consumers filter the information attained based on the data acquired in the previous phase. The fourth block of questions was constituted of five statements related to the Buying Decision phase of the buying decision process when it comes to having dinner in restaurants. It is the moment in which the consumers, after analyzing the alternatives available, decide about their purchase, having as basis objective and subjective criteria, such as those related to their social interactions and to the factors present in the company’s offer (Blackwell, Miniard & Engel, 2005; Gade, 1998;Garcia, Moreira, Lima & Galli, 2017; Hettiarachchi, ,Wickramasinghe, Ranathunga, 2017; Pankajakshi & Savitha, 2015; Oliveira, 2007). The fifth block of questions was constituted of five statements related to the Post- Purchase Behavior phase of the buying decision process when it comes to having dinner in restaurants. It is the phase in which the consumers, after acquiring the product, demonstrate their satisfaction or dissatisfaction with the purchase (Blackwell, Miniard & Engel, 2005; http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 475 Gade, 1998;Garcia, Moreira, Lima & Galli, 2017; Hettiarachchi, ,Wickramasinghe, Ranathunga, 2017; Pankajakshi & Savitha, 2015; Oliveira, 2007;Samara & Morsch, 2004; Solomon, 2003). For the data analysis, the research hypotheses will be verified through the analysis of the correlations, aiming to refute or accept them. The analysis of the correlations for the hypothesis H1 is demonstrated in Table 2. Table 2 – Spearman’s Rho PI x SI Correlations Problem Identification Search for Information Spearman’s Rho Problem Identification Correlation Coefficient 1.000 .315** Significance (1 extremity) .000 N 314 314 Bootstrap b Bias 0.000 .002 Standard Error 0.000 .054 Confidence Interval 95% Lower 1.000 .203 Upper 1.000 .414 Search for Information Correlation Coefficient .315** 1.000 Significance (1 extremity) .000 N 314 314 Bootstrap b Bias .002 0.000 Standard Error .054 0.000 Confidence Interval Lower .203 1.000 Upper .414 1.000 http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 476 95% **. The correlation is significant in the level 0.01 (1 extremity). b. Unless otherwise indicated, the automatic initialization results are based on 1,000 bootstrap samples Source: Research Data The results found in Table 2 demonstrate that there is a significant correlation lower than 0.001** between the variables Problem Identification and Search for Information. The value of the correlation between these two variables is 0.315, which demonstrates that the influence between the variables is 31.5, value that is considered moderate and significant. This relation corroborates the observations of Bettman (1998), Bhalerao, Pandey, Kumar (2017), Erasmus, Boshoff & Rousseau (2001), Farley & Ring (1970), Goldstein & Almeida (2000), Hunt & Pappas (1972), Kollat, Engel & Blackwell (1970), Lopes & Silva(2012), Mowen (1988), Nalini, Cardoso & Cunha (2013), and Richers (1984). Cobra (2011), Churchill & Peter (2003), Blackwell, Miniard & Engel (2005), Jisana (2014), Karslakian (2000), Kotler & Keller (2006), Limeira (2008), Longart, Wickens & Bakir (2016), Mowen (1988), Reade et al. (2015), Oliveira (2007), Samara & Morsch (2004) and Solomon (2003). According to these authors, this process starts with the problem identification by the consumers. Then, they notice they need to act. After verifying this need, they go to the Search for Information phase and try to find out which products meet their need (Blackwell et al., 2005; Cobra, 2011; Gade, 1998; Karsaklian, 2000; Limeira, 2008; Mowen, 1988; Oliveira, 2007; Solomon, 2003). The results found evidence of this relationship, and that there is an influence on the consumers' decision-making. The following step was verifying the validity of hypotheses H2. Due to the fact that there is a theoretical connection between the “Search for Information (SI)” and the http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 477 “Alternatives Analysis (AA)”, this hypothesis indicates that there is a correlation between these two processes. The values found are demonstrated in Table 3. Table 3: Spearman’s Rho SI x AA Correlations Search for Information Alternatives Analysis Spearman’s Rho Search for Information Correlation Coefficient 1.000 .401** Significance (1 extremity) .000 N 314 314 Bootstrap b Bias 0.000 .000 Standard Error 0.000 .049 Confidence Interval 95% Lower 1.000 .304 Upper 1.000 .497 Alternatives Analysis Correlation Coefficient .401** 1.000 Significance (1 extremity) .000 N 314 314 Bootstrap b Bias .000 0.000 Standard Error .049 0.000 Confidence Interval 95% Lower .304 1.000 Upper .497 1.000 **. The correlation is significant in the level 0.01 (1 extremity). b. Unless otherwise indicated, the automatic initialization results are based on 1,000 bootstrap http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 478 samples Source: Research Data The values found in Table 3 demonstrate that there is a significant correlation at a value lower than 0.001**, indicating that the hypothesis H0 (there is no correlation) is rejected, at a certainty rate of de 99%, with a moderate correlation of 0.401. This corroborates what Blackwell et al., 2005; Cobra, 2011; Gade, 1998; Jisana, 2014; Karsaklian, 2000; Kotler & Keller, 2006; Longart, Wickens & Bakir, 2016;Limeira, 2008; Mowen, 1988; Pankajakshi & Savitha, 2015; Oliveira, 2007; Reade et al., 2015; Samara & Morsch, 2004; Sheth et al., 1998 have affirmed: after the Search for Information process, the consumers start analyzing the alternatives, making decisions based on the competitors and the offers available, besides measuring their financial limitations. The correlation analysis has demonstrated that there is an average correlation between the two processes. The following step was testing the Hypothesis H3, to verify if there is a correlation between the processes "Alternatives Analysis (AA)" and "Buying Decision (BD)". The results are demonstrated in Table 4. From the data in Table 4, we can verify that the hypothesis H0 is rejected, since there is a significantly lower than 0.001** for the correlation between the Alternatives Analysis and the Buying Decision, and there is an average effect of 0.306 in this correlation. The results found confirm what Karsaklian (2000), Reade et al. (2015), and Samara & Morsch (2004) have claimed: the consumers buy after undergoing the previous phases. The ideas of Kotler & Keller (2006) have also been endorsed: in the Alternatives Analysis stage, the consumers create preferences amidst the brands of the range of choices. http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 479 Table 4: Spearman’s Rho AA x BD Correlations Alternatives Analysis Buying Decision Spearman’s Rho Alternatives Analysis Correlation Coefficient 1.000 .306** Significance (1 extremity) .000 N 314 314 Bootstrap c Bias 0.000 -.001 Standard Error 0.000 .055 Confidence Interval 95% Lower 1.000 .187 Upper 1.000 .409 Buying Decision Correlation Coefficient .306** 1.000 Significance (1 extremity) .000 N 314 314 Bootstrap c Bias -.001 0.000 Standard Error .055 0.000 Confidence Interval 95% Lower .187 1.000 Upper .409 1.000 **. The correlation is significant in the level 0.01 (1 extremity). c. Unless otherwise indicated, the automatic initialization results are based on 1,000 bootstrap samples Source: Research Data http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 480 The results also allow us to conclude that, after that, the decision about the purchase is made, and other three factors acting over the perception will also affect the decision: the attitude of the others, unforeseen situational factors and the perceived risk (Blackwell et al., 2005; Cobra, 2011; Gade, 1998; Limeira, 2008; Mowen, 1988; Oliveira, 2007; Solomon, 2003; Rainbolt, Onozaka, & McFadden, 2012). Finally, the hypothesis H4, which measures the correlation existing between the Purchase Decision and the Post-Purchase Behavior, has been assessed. The data are displayed in Table 5. Through the analysis of Table 5, we can notice that the correlation between the Buying Decision and the Post-Purchase Behavior is significant at a value lower than 0.001, allowing a hit probability of over 99% when rejecting the hypothesis H0 – “There is no correlation between the variables”. Moreover, the correlation existing between the variables is considered moderate, with a 0.321 (32.1%) influence value between such processes. This aspect is corroborated by Blackwell et al., 2005; Cobra, 2011; Gade, 1998; Jisana, 2014; Karsaklian, 2000; Kotler & Keller, 2006; Longart, Wickens & Bakir, 2016;Limeira, 2008; Mowen, 1988; Pankajakshi & Savitha, 2015; Oliveira, 2007; Reade et al., 2015; Samara & Morsch, 2004; Sheth et al., 1998, who have affirmed that, in order to reach this stage, the consumer undergoes the previous phases, and that, in spite of being the last one, this part is not the least important, since it aims to retain the consumers’ loyalty, so that they buy again and make positive comments about the organization, which will necessarily make them suggest the products to their peers. http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 481 Table 5: Spearman’s Rho BD x PPB Correlations Buying Decision Post- Purchase Behavior Spearman’s Rho Buying Decision Correlation Coefficient 1.000 .321** Significance (1 extremity) .000 N 314 314 Bootstrap c Bias 0.000 -.001 Standard Error 0.000 .056 Confidence Interval 95% Lower 1.000 .212 Upper 1.000 .432 Post- Purchase Behavior Correlation Coefficient .321** 1.000 Significance (1 extremity) .000 N 314 314 Bootstrap c Bias -.001 0.000 Standard Error .056 0.000 Confidence Interval 95% Lower .212 1.000 Upper .432 1.000 **. The correlation is significant in the level 0.01 (1 extremity). c. Unless otherwise indicated, the automatic initialization results are based on 1,000 bootstrap samples Source: Research Data http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 482 Accordingly, all hypotheses have been accepted, which has led to the model validation in the face of the sample. Figure 4 demonstrates the final buying decision model. Figure 4 – Final Buying Decision Model Source: Research Data Figure 4 shows the hypotheses proposed by the theoretical model, as well as the ways proposed and the final validation of the model. The values of the correlations and the significance levels for each hypothesis tested and validated are also demonstrated. The confirmation of all hypotheses indicates that the consumers’ behavior model evidenced in this paper is quite consistent, proving that the distinct phases from the choice to the buying decision are sequential and, therefore, may be characterized as an excellent managerial tool for actions related to the client’s understanding. http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 483 Conclusions In markets increasingly more competitive, thinking in terms of Marketing may be a considerable differentiating factor so that the companies manage to keep competitive. Thus, when a company thinks of Marketing (not only of its strategies, but also of its way of relating with the market), it is expected that its entire effort focuses on satisfying the consumers' needs and wishes, as proposed by Cobra (2011), Kotler & Keller (2006), Pankajakshi & Savitha, (2015), Reade et al. (2015), and Oliveira (2007). However, in order that the consumer’s needs and wishes are understood in a strategic fashion, and that the products and services meet them, it is important to conduct a proper study on the consumers’ behavior, that is, to realize how they select, buy, use and discard goods, services, ideas or experiences in order to satisfy their needs and wishes (Gade, 1998; Kotler & Keller, 2006). Aware of this importance, this paper has investigated the food and beverage sector with the main purpose of understanding the consumers' behavior about their buying decision process. Aiming to achieve this purpose and to notice this process in a more assertive way, it was decided to investigate the choice of restaurants to have dinner. The buyer decision processes is stimuli under differing involvement conditions (Montandon, Ogonowski, & Botha, 2017). A quantitative research has tried to evidence the theoretical correlation among the phases described in the buying decision process, based on the model by Blackwell, Miniard & Engel (2005), which proposes that the consumers undergo the following phases when making a decision and their purchase: Problem Identification, Search for Information, Alternatives Analysis, Buying Decision and Post-Purchase Behavior as they claim (Bettman (1998), Bhalerao, Pandey, Kumar (2017), Erasmus, Boshoff & Rousseau (2001), Farley & http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 484 Ring (1970), Goldstein & Almeida (2000), Hunt & Pappas (1972), Kollat, Engel & Blackwell (1970), Lopes & Silva(2012), Mowen (1988), Nalini, Cardoso & Cunha (2013), and Richers (1984). Cobra (2011), Churchill & Peter (2003), Blackwell, Miniard & Engel (2005), Jisana (2014), Karslakian (2000), Kotler & Keller (2006), Limeira (2008), Longart, Wickens & Bakir (2016), Mowen (1988), Reade et al. (2015), Oliveira (2007), Samara & Morsch (2004) and Solomon (2003). The research conducted was characterized as empirical with a quantitative approach. As to the research procedures, the bibliographic and field analysis methods have been used. For the field analysis, a questionnaire based on the Likert scale has been prepared to be replied to through the researchers’ social network. The number of respondents was 383 people. Since the questionnaire has been designed using the Likert scale, it adopts the Spearman’s Rho correlation coefficient. Through these procedures, it was possible to validate the hypotheses raised in this article and to prove the relation existing between the model proposed and the consumers’ behavior when choosing restaurants to have dinner. When directing the research, the following hypotheses have been raised: H1: there is a relation between the “Problem Identification (PI)” – the moment when the consumers realize they have an unmet need, triggering all the subsequent phases (Blackwell et al., 2005) – and the “Search for Information (SI)” – situation in which the consumers seek information to resolve their problems (Karsaklian, 2000). This hypothesis has been supported according to the method proposed, showing that there is a relation between these two stages. H2: there is a theoretical relation between the “Search for Information (SI)” and the “Alternatives Analysis (AA)" – the moment when the consumers, having the information collected as a basis, filter the data to facilitate their decision (Limeira, 2008). This hypothesis http://ertr.tamu.edu/ e-Review of Tourism Research (eRTR), Vol. 16, No. 5, 2019 http://ertr.tamu.edu 485 has been proved, revealing that there is a correlation between these two processes, or phases, described in the literature. H3: there is a correlation between the “Alternatives Analysis (AA)" and the "Buying Decision (BD)" – the moment when the consumers decide among the existing alternatives (ROCHA, 2015). This hypothesis has also been supported during the investigation. A correlation between these phases has been evidenced by the analysis of the data obtained. H4: there is a correlation between the "Purchase Decision (PD)" and the "Post- Purchase Behavior (PPB)" – the final result of the process, in which the consumers will be satisfied or dissatisfied with their acquisitions. This hypothesis has also been confirmed, that is, the Buying Decision influences the Post-Purchase Behavior. The confirmation of these hypotheses in the food and beverage sector, particularly in the choice of restaurants to have dinner, shows not only the correlation between the phases of the process presented in the literature and the validation of a renowned model, but also the importance of the managers’ analysis of these processes in a systematic fashion. This means that there are correlated processes that are not to be considered separately when studying the consumers’ behavior. It is important to understand these factors in a synergic way, perceiving that possible failures in one of the phases may affect the whole process. It is believed that the results may help managers realizing the consumers’ behavior, especially their buying decision process. 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