1. INTRODUCTION

Over the past six decades, international tourism has become one of the fastest growing sectors of the economy in the world. According to the World Tourism Organization (UNWTO – 2015), the number of international tourists arriving in countries around the world (and staying overnight) increased from 25 million in 1950 to 1.133 billion in 2014 and the revenue from international tourism reached the value of US$ 1.245 trillion worldwide. The number of international tourists around the world is expected to grow 3.3% per year, reaching 1.8 trillion in 2030.

Due to the growth of the tourism sector in the world and its increasing relevance in the economy of several countries, the number of academic research related to the subject has increased in the last decades, including in the social sciences. According to Sampaio (2013), as tourism has become a broad social practice since the second half of the twentieth century, there are many conferences and specialized publications on the subject in social sciences, based on the most diverse perspectives. In Administration – an applied social sciences area – there is also great interest in the subject of tourism, especially in studies related to consumer behavior. Correia and Pimpão (2008) argue that, with the global development of tourism, understanding consumer behavior is fundamentally important, since the strategic management of tourist destinations depends on the development of theories about consumer behavior and the understanding of tourists' choices.

The destination choice or choice process is a frequent topic in studies on consumer behavior in tourism as it is associated with creating and keeping demand related to the destinations and tourist services offered. Given the importance of this topic, this bibliographic study aims to identify the main subjects and authors related to the topic and, at the same time, understand the main discussions and relations established between them. Thus, a search for articles was carried out in the database Scopus. Articles were then selected through the statistical tool SciMat (Cobo et al., 2012) and analyzed – quantitatively and qualitatively. The study shows that, in the context of destination choice, research is elaborated by using diverse theoretical approaches and references, besides being carried out in different schools and countries, which demonstrates the global interest on the topic.

2. TOURISM DESTINATION CHOICE

The literature on tourism has many works related to the study of consumer behavior that describe tourists’ decision-making processes. Sirakaya and Woodside (2005) evaluated the main models of decision making in the literature on tourism and concluded that most of them understand the selection process (or choice process) as a funnel, in which travelers, based on rational behavior, eliminate alternatives based on socio-psychological and non-psychological factors. According to the study, the factors that determine the set of alternatives and choices can be divided into four groups, and the destination choice depends on the nature of interaction between these variables: (1) internal variables (attitudes, values, lifestyle, image, motivation, life cycle, risk reduction, etc.), (2) external variables (pull factors of the destination, family, friends, culture, reference groups, etc.), (3) the nature of the intended trip (holiday, size, distance, duration of trip, etc.), and (4) travel experiences (mood and feelings during the trip, post-purchase evaluations, etc.). Similarly, Jang and Cai (2002) state that, although there is no unified perspective, an approach that effectively explains tourists' travel motivations assesses the factors that drive (push motives) and attract (pull motives) tourists to a specific destination. Push motives correspond to internal and emotional variables that lead potential tourists to make travel decisions, explaining the desire to travel and the destination considered, for example, relaxation, social interaction, search for knowledge, social recognition, and adventure. Pull motives are linked to external aspects, motivations inspired by the attractiveness of a destination, such as natural environment, social environment, shopping, gastronomy, and cultural and historical attractions. For Karl, Reintinger, and Schmude (2015), in addition to the characteristics of tourists, restrictions related to the destination also play an important role in the selection or rejection of destinations during the decision-making process. Restrictions vary according to the type of destination and are more related to the destination than to the tourist. Financial restrictions (usually linked to travel distances and means of transport, since long-distance trips are associated with high travel expenses), lack of holidays, impossibility of finding a suitable travel partner, dangers, and political situation in the destination are examples of restrictions.

Regarding the choice process, Sirakaya and Woodside (2005) mention two predominant approaches in the literature. One of them is called "behavioral approach" and it was originated from the general models of consumer behavior such as those presented by Engel, Kollat, and Blackwell (1973), and Howard and Sheth (1969). This approach suggests that tourists are motivated by several factors when selecting and choosing different alternatives that can meet their needs; and the models focus on the buying process, in which the tourist is exposed to information, searches for more information, evaluates alternatives, and finally choose one of them. The main proposal of the behavioral models is to identify the stages of decision and design in this process, identifying the internal and external factors that influence it. One of the most recognized models of this approach is the one proposed by Moutinho (1987), which presents a three-part flowchart (pre-decision and decision-making processes, post-purchase evaluation, and future decision making) that describes the process tourists went through and the variables that influence decisions related to the purchase and repurchase of trips and holiday destinations. Environmental influences, personal factors (personality, lifestyle, motivation), attitude, influence of the family, inhibiting and risk factors, and satisfaction/dissatisfaction with the trip are some of the main variables.

The other approach is called the "choice-set." Despite accepting most of the assumptions of the behavioral approach, it is different, simpler, and more practical, since it proposes that the tourist defines an initial set of options of destination and then eliminates some of them over time until making a final choice. In this approach, the focus is not on the decision-making process, but on the psycho-behavioral variables and how consumers begin to have cognitive and affective judgments, intentions, and commitments before making a final decision. For Woodside and Lysonski (1989), variables of the marketing mix have an external influence, while variables of the tourist (experience in the previous destination, life cycle, income, age, lifestyle, and value system) represent internal variables. Both affect destination choices, which are categorized into different sets (considered, inept, inert, and unavailable/conscious) that, along with affective associations related to the destination, influence preferences, intention, and destination choice. Um and Crompton (1990) present a simpler model, in which external factors – meaningful, symbolic, and social stimuli – influence the cognitive construction of the tourist’s set of potential destinations (awareness set). These external factors, along with internal factors – personal characteristics, motivation, values, and attitudes – influence the cognitive development of a second set of potential destinations (evoked set) in the tourist’s mind, from which they select and choose the destination.

These models, however, are criticized by Decrop (1999) and Decrop and Snelders (2004), who believe there is not one but several ways of understanding decision-making processes and behavior. For them, the traditional models of Moutinho (1987), Um and Crampton (1991), and Woodside and Lysonski (1989) are based on positivist paradigms, (limited) rationality, and the cognitive processing of information; and they misread the complexity of real life and misrefer important issues – such as the role of emotions and feelings, low involvement and passive search for information, nostalgia, dreams, etc. They also criticize the fact that these models mainly consider the individual’s choice process as, in tourism, decisions depend on the individual, group, and moment. After analyzing the existing decision models, Sirakaya and Woodside (2005) seem to agree with the critics, suggesting that in real situations the models of choice sets may serve more as probabilistic than deterministic models; and that new, more simple, specific, and applicable destination choice models should be created by considering the differences in the nature and purpose of each type of trip, the role played by emotions in decision-making process – which is often not entirely rational because it is tourism – and group decision making.

Considering the role of emotions in travel destination choice, there is in the literature a discussion about the influence of self-congruity – proximity or distance between the tourist’s self-image and the image they attributed to the destination – as a motivating factor. The closer the tourist’s self-image is to the image they attributed to the destination, the more favorable attitude towards the destination and, consequently, the greater the possibility of visiting it. Some studies (Sirgy, 1997; Beerli, Meneses, & Gil, 2007; Boksberger, Dolnicar, Laesser, & Randle, 2011; Usakli & Baloglu, 2011) demonstrate the influence of self-congruity on decisions related to travel destination choice. Other research, also related to the congruence between the tourist and the destination, show that the relation between the tourist’s characteristics and holiday destination determines satisfaction (Bekk, Spörrle, & Kruse, 2016) and fidelity (Ekinci, Sirakaya-Turk, & Preciado, 2013).

Regarding the decision-making process, it should be noted that decisions are not always individually made, and individuals or groups that influence the process must be evaluated. Stone (2016), for example, states that, instead of making their own decisions, part of the tourists delegate decisions about where to go, what to do, and where to eat with people whom they travel with. In the survey conducted, an average of 25% of people delegated travel destination decisions to their fellow travelers. For Shu and Scott (2014), influencers are not only close people or fellow travelers but also social media, which play a role in building the attractiveness of the destination, generating positive or negative impressions that influence tourists’ travel destination choice.

3. RESEARCH METHODOLOGY

This study used bibliometric techniques, tools, and indicators. Cronin (2001) argues that bibliometric studies have traditionally focused on tracking highly visible indicators and academic activity’s objectives – publications and citations. The most used bibliometric indicators are those of scientific performance of organizations, agencies, and countries, based on publication and citation counts in the scientific literature (Narin & Hamilton, 1996). Regarding the method, Wallin (2005) states that bibliometric studies include study publication patterns, “bibliographing” – counting the number of abstracts and bibliographic indexers or databases that record the content of the journal), bibliographic coupling – co-citation and co-occurrence – and citation analysis of articles and scientific patents. Although bibliometric methods are quantitative, they are used to make pronouncements on qualitative characteristics. The main purpose of all types of bibliometric exercises is to transform something intangible into a manageable entity (Wallin, 2005).

To obtain the data and information necessary for this study, the Scopus database was used, which is the largest number for tourism and hospitality journals (Hall, 2011), and a high correlation of papers and citations (Archambault, 2009) compared to the traditional database Thomson ISI Web of Knowledge. The search was carried out on June 6, 2016 and used the keywords “tourist destination,” “destination choice,” “tourist decision,” and “tourist choice.” This led to 13,239 documents being found. This result was filtered by the areas of business, management, and accounting (6,753 documents) as well as document type, with only scientific articles (5,760 articles) being selected. Then, only articles published in journals classified in the first quartile (Q1) of the SCImago Journal Rank (SJR) indicator (2015) in the category Tourism, Leisure and Hospitality Management were selected – Tourism Management, Annals of Tourism Research, Journal of Sustainable Tourism, Asia Pacific Journal of Tourism Research, Journal of Travel and Tourism Marketing, International Journal of Tourism Research, Journal of Vacation Marketing, Tourism Management Perspectives or International Journal of Hospitality Management, Journal of Hospitality Marketing and Management, Journal of Hospitality and Tourism Research, International Journal of Contemporary Hospitality Management. The restriction based on the main journals of the area, according to the SCImago Journal Ranking (Table 1), resulted in 2,222 articles, which were ordered by the number of citations indicated in the database. The 2,000 articles most cited were selected (maximum limit established by the Scopus database for exporting data in a single file) to compose the sample for the first analysis. The use of citation as a selection criterion for the sample’s articles is based on the arguments defended by Bornmann et al. (2008), who consider citations as indicators of research impact – that is, how useful it has been to other researchers – and by Van Raan (2004), who says that bibliometric analysis based on number of citations provides indicators of impact and international influence.

The first analysis of the sample used the software SciMat (Cobo et al., 2012). Relevant information can be obtained from the co-occurrence frequency of keywords, which were extracted from the database by counting the number of documents in which the two keywords appear together. At the end of the process, clusters are formed and they can be understood as semantic or conceptual groups of the different topics addressed by the research field, and used for several purposes, such as the quantification of the research field (Cobo et al., 2011). The software identifies the keywords of each article and forms groups based on them. The distances between these groups are defined by the frequency of keywords appearing together in each record of the database. For example, clusters formed by the keywords “decision making” and “travel behavior” may be closer or farther, depending on the number of times both keywords are found in the articles that make up these clusters.

In the database, 6,282 clusters were found based on the co-occurrence of keywords. The main clusters can be seen in Figure 1.

In the search for the most relevant clusters, 6,065 clusters were excluded because they were based on keywords that are non-significant for this study (e.g., name of countries, areas of administration, and denominations of research methods) and composed of less than 10 articles. From 217 remaining clusters, two presented greater adherence and concentration of relevant articles on the topic and were therefore chosen for in-depth analysis on “decision making” (112 articles) and “destination choice” (36 articles). Finally, these articles were identified and separated. After eliminating duplicate records, the final sample of 141 articles was formed, which was used as the source of analysis and results presented in the next sections.

4. RESEARCH RESULTS

Based on the sample of 141 articles, analyzes and surveys of bibliometric indicators were carried out to better understand the topic addressed in this study. Regarding the year of publications, there is a growing trend in the number of articles published in the journals selected from 1997, peaking in 2012 and decreasing again until 2015 (Figure 2). Few articles were published annually by 1996, and most of the most cited articles in the database were published between 2000 and 2010 (Table 2). The data indicate that this is a topic of recent interest, with publications of greater impact concentrated in the last decade.

Regarding the source of the publications, 90.1% of them were concentrated in five journals, with emphasis on the Tourism Management Journal, which has 41.8% of all the publications (Table 3).

There is no great concentration when considering the ranking of institutions linked to the research. The institutions with the highest number of publications have, at most, three or four published works, except for the School of Hotel and Tourism Management, with seven published articles (Table 4). An evaluation carried out in the database indicates that most of the listed institutions are related to a single article.

A qualitative content analysis was then performed in the abstract of the 24 most cited articles of the sample (Table 5); that is, articles with up to 1% of the total citations. The result shows that the main issues addressed in this group are:

• Models of decision or destination choice (five articles);

• Motivating factors for tourism (four articles);

• Decisive personal characteristics or factors related to the destination choice (four articles);

• Influence of information and communication on the destination choice (four articles);

• Influence of destination’s image (two articles).

Also based on the sample, an analysis of clusters was performed by using the software SciMat (Cobo et al., 2012). Based on co-occurrence of keywords, 805 clusters were found. Figure 3 shows the main clusters and Table 6 presents the number of articles in each cluster.

As the subject of this study is the destination choice, a qualitative content analysis was carried out with the abstract of the 35 articles in the cluster destination choice (Table 7). The main issues addressed by the articles in this cluster are:

• Models of decision making or destination choice (five articles);

• Motivating factors for tourism (six articles);

• Decisive personal characteristics or factors related to the destination choice (seven articles);

• Decisive destination characteristics or appeals to the destination choice (three articles);

• Influence of the destination’s image (three articles);

• Influence of information and communication on the destination choice (two articles).

The content analyzes both of the sample’s most relevant articles and the totality of the cluster “destination choice” present similar results in relation to the subjects discussed. Therefore, considering the two analyses, there are indications that the main subjects addressed in research related to "travel destination choice" are: (a) decision models or destination choice, (b) motivating factors for tourism, (c) decisive personal characteristics or factors related to destination choice, (d) decisive destination characteristics and attractiveness to the destination choice, (e) influence of the destination’s image, and (f) influence of information and communication on the destination choice. These subjects may be used, partially or completely, by researchers who wish to carry out a complete study on the topic. The items a, b, c, and d are mentioned by Sirakaya and Woodside’s (2005) study as main components of decision-making models in tourism; while items e and f were not highlighted by them. Regarding these two items, it is important to emphasize that, although some articles (Phelps,1986; Fodness & Murray, 1997; Vogt & Fesenmaier, 1998; Decrop & Snelders, 2004) were published before their study, most of the articles addressing these topics (Prentice & Andersen, 2000; Glover, 2011; Kerr, Cliff, & Dolnicar, 2011; Park & Nicolau, 2015; Molina & Esteban, 2006; Yüksel & Akgül, 2007; Jacobsen & Munar, 2012) were published after the survey carried out by Sirakaya and Woodside (2005). Likewise, the groups of determining factors related to destination choice identified by these authors as "nature of the intended trip" (holiday size, distance, duration of the trip, etc.) and "travel experiences" (mood and feelings during the trip, post-purchase evaluations, etc.) were not highlighted either in cluster formation or content analysis, although there were articles related to these subjects in the sample collected.

4.1 Citation analysis

This section presents analysis based on the citations of articles and authors within the articles that compose the sample.

For Bornmann et al. (2008), the publication of a research paper serves to disseminate its results, inviting other scientists to use them in their own research, which is indicated by a formal citation. Citations show that a publication used other publications’ content (results and ideas) and, therefore, citation counts are used to measure the impact of research; that is, how useful it has been to other researchers. Similarly, Van Raan (2004) states that citation-based bibliometric analysis provides indicators of international impact and influence, since citation counts have been used to evaluate and compare the performance of individual researchers, research departments and institutions, as well as the scientific impact of nations.

However, citation analysis has limitations. Bornmann and Daniel (2008) argue that citations are not only motivated by the desire to recognize intellectual and cognitive influences of fellow scientists, since individual studies also reveal other non-scientific factors that play a role in the decision to cite – such as social factors, author’s location and prestige, language and availability of journals for publication (Bornmann et al., 2008). Despite this, citation measures have been demonstrated to be a valid form of peer judgment that introduces a useful element of objectivity into the assessment process and involves only a small fraction of the cost of surveying techniques (Garfield, 1979).

Table 8 shows the most cited articles by the authors in the sample’s articles. In addition to the main topics already identified and discussed in this study, others were included: statistical analysis (Hair et al., 1998; Fornell & Larcker, 1981), consumer behavior (Engel et al., 1973; Howard & Sheth, 1969) as well as psychological (Mayo & Jarvis, 1981; Fishbein & Ajzen, 1975; Ajzen & Fishbein, 1980) and cultural factors (Hofstede, 1980) that affect consumer or, specifically, tourist behavior.

Crompton and Woodside stand out as the authors of the most cited articles (Table 9). There are also authors (and articles) of the tourism area who are much cited but are not part of the sample, such as Daniel R. Fesenmaier, J.R. Brent Ritchie, Dale Fodness, Abraham Pizam, and Luiz Moutinho.

4.2 Co-citation analysis

This section presents the result of the co-citation analysis, based on the references indicated in the articles of the sample. For Small (1973), co-citation is the frequency with which two previous items are cited together in a later literature. The number of citations of two identical items defines the strength of the co-citation and, consequently, the degree of relation or association between two articles; that is, how they are perceived by a group of authors.

Therefore, co-citation patterns can be used to map in detail the relations between key concepts, methods, or experiments in a field of knowledge. This perspective is reinforced by Wallin (2005), who states that the greater the number of researchers citing the same two publications, the greater the probability that the double citation is not a fortuitous event, expressing a type of related subject between the cited publications, establishing visible relationships within the research areas and between scientific disciplines.

Figure 4 shows the main co-citations based on the references of the articles in the sample. Cross analysis, performed with the 10 most cited authors in the references, showed that John L. Crompton and Arch Woodside are the most cited authors. Crompton and Woodside present similar decision-making models and destination choice based on choice-sets, which are influenced by various personal and external factors.

In studies involving destination’s image, which use Ritchie’s articles, the authors Crompton, Woodside, and Fesenmaier can be used to present and discuss models of decision-making process. Similarly, both works that study memory and familiarity with the destination (citing Pizam) and that involve the influence of information processes on the destination choice (citing Fodness) can use Crompton and Woodside’s studies as a model for the destination selection process. Finally, the relationship between Decrop and the authors Crompton and Woodside can be established due to the critical position of the first author in relation to the others. Therefore, Decrop’s articles can be used to found the criticisms to Crompton and Woodside’s models.

5. FINAL CONSIDERATIONS

Destination choice in tourism can be studied from different perspectives, using theoretical approaches and foundations originated in different areas of science. Some studies are founded in economics, calculating demand through econometric models.

However, most research in the area studies the psychological and social aspects involved in decision making, whether focusing on the decision process itself (consumer behavior models) or studying the main psycho-behavioral variables and how tourists make cognitive and affective judgments before making the final decision.

The bibliographic study demonstrates the diversity of perspectives and approaches by identifying groups of studies related to decision models or destination choice; motivating factors for tourism; personal characteristics or factors; destination’s characteristics and attractiveness; nature of the intended trip (holiday size, distance, duration of the trip, etc.); travel experiences (feelings during the trip, post-purchase evaluations, etc.); influence of the destination’s image; and influence of information/communication on the travel destination choice. Although there are prominent authors, such as Crompton and Woodside, this study also shows they are not mentioned in most of the studies evaluated, which proves the difference in theoretical references related to the topic.

Because of the diversity of approaches and perspectives on the topic, this study needed to filter the articles for analysis. The first restriction was the selection of articles published only in the main journals, according to the SCImago Journal Ranking (SJR). The second restriction, established by the database itself, was the limitation of the number of articles that compose the sample; the first 2,000 articles were selected and classified according to the number of citations, from the most cited to the least cited. Finally, the last restriction was the analysis of citations and co-citations only for the cluster denominated "destination choice." Considering these restrictions, there may be articles and authors discussing subjects related to the topic that are not contemplated in this analysis, which is the main limitation of this research. In addition, the citation analysis technique has its own limitations. According to Bornmann and Daniel (2008), citations are motivated by the desire to recognize intellectual and cognitive influences of fellow scientists, since individual studies also reveal that other non-scientific factors – such as social factors, author location and prestige, language, and availability of journals for publication – play a role in the decision to cite. These limitations, however, do not invalidate the main conclusions of this study; on the contrary, they demonstrate that the diversity of approaches allows future research to continue exploring the topic in the search for other theories and theoretical references.

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Author notes

csaito@espm.br

Additional information

To cite this article: Saito C. S.; Strehlau V. I. (2018) Tourist destination choice: A bibliometric study. Internext – Review of International Business, 13 (1), 17-31. DOI: http://dx.doi.org/10.18568/1980-4865.13117-31