Determinant Competitiveness Attributes of Brazilian Sun and Sand Destinations^*

Atributos Determinantes de la Competitividad de los Destinos de Sol y Playa Brasileños

Abstract

Destination competitiveness models reached a development level in which all the characteristics that somehow influence competitiveness were mapped, albeit without identifying which factors are decisive for competitiveness (Crouch, 2011). We used the Qualitative Comparative Analysis (QCA) technique, adopting the domestic and international tourist inflows as criteria variables for identifying which competitiveness dimensions are decisive for Brazilian sun and sand destinations. Our results suggest that Access, Cultural Aspects, Local Economy, and Business Capacity dimensions have a greater influence on destination performance. In addition, the results indicate that it is not necessary to have a high level of development in many dimensions to achieve higher performance. Results provide practical guidance for sun and sand destination management.

Keywords:
Destination; Competitiveness; Strategy; Qualitative comparative analysis - QCA

Resumen

Los modelos de competitividad de destinos turísticos alcanzaron un nivel de desarrollo en el que todas las características que de alguna forma influencian la competitividad fueron mapeadas, pero sin identificar qué factores son decisivos para la competitividad (Crouch, 2011). La técnica Análisis Comparativo Cualitativo fue empleada para identificar cuáles dimensiones de competitividad son decisivas para los destinos de sol y arena brasileños, adoptando los flujos de turistas domésticos e internacionales como variables criterio. Nuestros resultados sugieren que las dimensiones Acceso, Aspectos Culturales, Economía Local y capacidad empresarial tienen mayor influencia en el desempeño de los destinos. Además, los resultados indican que no es necesario tener un alto nivel de desarrollo en un gran número de dimensiones para obtener un rendimiento superior. Los resultados proporcionan orientación práctica para la gestión de destinos de sol y playa.

Palabras clave:
Destino turístico; Competitividad; Estrategia; Análisis comparativo cualitativo - QCA

Resumo

Os modelos de competitividade de destinos turísticos alcançaram um nível de desenvolvimento em que todas as características que de alguma forma influenciam a competitividade foram mapeadas, sem, no entanto, identificar quais fatores são decisivos para a competitividade (Crouch, 2011). A técnica QCA (Análise Comparativa Qualitativa) foi empregada para identificar quais dimensões de competitividade são decisivas para os destinos de sol e areia brasileiros, adotando os fluxos de turistas domésticos e internacionais como variáveis critério. Nossos resultados sugerem que as dimensões Acesso, Aspectos Culturais, Economia Local e Capacidade Empresarial têm maior influência no desempenho dos destinos. Além disso, os resultados indicam que não é necessário ter um alto nível de desenvolvimento em um grande número de dimensões para obter um desempenho superior. Os resultados fornecem orientação prática para a gestão de destinos de sol e praia.

Palavras-chave:
Destino turístico; Competitividade; Estratégia; Análise comparativa qualitativa - QCA

1 INTRODUCTION

Although destination competitiveness remains a central issue (Camisón & Forés, 2015; Domareski-Ruiz, Akel & Gândara, 2015;), it still lacks a consensual definition (Crouch & Ritchie, 1999; Carmona, Costa & Ribeiro, 2014; Sette, Santos & Uvinha, 2017). Some definitions highlight the destination capacity to create new products that add value to their resources and maintain their market position (Crouch & Ritchie, 1999; Hassan, 2000). Others describe competitiveness as the attractiveness and uniqueness of the experience provided (Crouch & Ritchie, 1999; Dwyer & Kim, 2003). According to Ritchie and Crouch (2010), destination competitiveness relates to the efficiency and effectiveness in which destination resources are deployed to generate growth and development in the sector. Similarly, the World Economic Forum-WEF-associates destination competitiveness with the increasing ability to generate business in tourism related activities (WEF, 2015).

Despite the absence of a common definition (Añaña, Pereira & dos Anjos, 2015; Sette & Tomazzoni, 2017; Sette; Santos & Uvinha, 2017), there seems to be an agreement on the perspective that competitiveness is multidimensional and relative (Crouch and Ritchie, 1999; Dwyer and Kim, 2003). Multidimensionality refers to the different aspects and indicators that might be used to assess competitiveness. Since the earliest models, different aspects have been introduced into the discussion about destination competitiveness. Therefore, the explanatory capacity of models increased as well as their complexity. This growing complexity makes it difficult to identify which dimensions are determinant to destination competitiveness (Crouch, 2011). Several aspects may be relevant for destination competitiveness, but only a few can be decisive (Crouch, 2011).

Besides multidimensionality, destination competitiveness is also relative. Tourism is an economic activity and destination success or failure is achieved through the destination performance in the market. No destination is competitive by itself or in isolation since competitiveness is a comparative concept. In this sense, destination competitiveness ought to be assessed vis-à-vis competitors. From these arguments, one may criticize studies that make wide and unrestricted comparisons between countries or destinations-such as the Travel and Tourism Competitiveness Report (World Economic Forum, 2015) or the Brazilian Competitiveness Model (MTur, SEBRAE & FGV, 2013)-since the compared destinations are from different market segments and do not effectively compete among themselves. Therefore, the results provided are at least questionable for guiding the management of specific destinations.

Considering the arguments presented, this research aims to identify the competitive dimensions that are decisive for the performance of 27 sun and sand Brazilian destinations in domestic and international demand. By aiming at a specific market segment, the paper provides a more insightful perspective for sun and sand destinations identifying which competitiveness dimensions are effectively relevant for their management. To achieve the objective, the paper is divided into 5 distinct sections, apart from the introduction. The following section reviews the main destination competitiveness models developed. The third section introduces the research method. The fourth section presents and discusses the results. Lastly, the conclusions are drawn.

2 DESTINATION COMPETITIVENESS MODELS

Camisón and Forés (2015) identified three competing approaches to competitiveness. The first one is associated with the territory and the comparative advantages of the geographical location. The second one relates to the structure-conduct-performance paradigm and considers competitiveness as an outcome of the industry structure. The third approach originates from the resource-based view (RBV) and focusses on the assets available for the firm (Barney, 1991). Even though these approaches provide insightful perspectives for destination competitiveness analysis, the tourism sector presents some peculiar characteristics (Hassan, 2000; Dwyer & Kim, 2003). Tourism services are consumed in situ (Ritchie & Crouch, 2010), and as such, they depend on the involvement of a diverse range of local companies, organizations, and local attractions (Hassan, 2000; Dwyer & Kim, 2003). Thus, local aspects ought to be considered when analyzing a destination.

In this sense, competitiveness refers not only to the companies directly associated with the tourism industry but also to the whole set of relationships able to foster synergies and promoting the competitiveness of firms and the local development. The destination competitiveness models follow this perspective due to the diversity of industries involved in the sector (Hassan, 2000), and the necessity to include different and related social actors in the analysis (Crouch & Ritchie, 1999). Destination competitiveness models, therefore, require a systemic perspective.

The Calgary model (Crouch & Ritchie, 1999) starts from a systemic perspective and associates the concept of destination competitiveness with its capacity to contribute to the local economy and to increase population well-being. Tourism success should not be analyzed in isolation since it is directly related to the performance of organizations and other economic and social sectors. In order to achieve success, tourist destinations should ensure their attractiveness and the uniqueness of the experiences provided to their visitors (Crouch & Ritchie, 1999).

According to Crouch and Ritchie (1999), destination competitiveness results from the interaction of four dimensions: Core Resources and Attractors, Supporting Factors and Resources, Destination Management, and Qualifying Determinants. These dimensions are directly influenced by macro and micro-environmental aspects. The macro-environmental aspects represent the possible environmental, political, and economic externalities to which the destination is susceptible. Competitive micro-environmental aspects are represented by the tourism business sector of the destination, as well as by local public agencies, their stakeholders, and other competing tourism destinations. In the latest version of the Calgary model (Ritchie & Crouch, 2010), the Policy and Planning dimension was integrated, which expanded the number of dimensions considered.

Crouch and Ritchie (1999) acknowledge that their model is neither predictive nor causal, but only explanatory and that it still requires further development before generalization can occur. Among its main limitations, it is mentioned the difficulty of measuring the components, due to the lack of statistical information in several destinations, the lack of a hierarchy between the components; and it fails to perform a more detailed examination of impacts of macro-environmental factors on destination competitiveness (Crouch & Ritchie, 1999; Taberner, 2007). Costa and Hoffmann (2006) point out that the proposed model presents a qualitative leap in the construction of a competitiveness model, but it is still limited to the empirical application due to the absence of indicators.

Kozak and Rimmington (1999) examined destination competitiveness from data obtained in a survey with tourists during their stay in a destination. The objective was to collect information about the diverse attributes of the tourist offer and the motivations for choosing a destination. Kozak and Rimmington (1999) focused on how demand aspects influence destination competitiveness. Among the limitations of their study are the impossibility of identifying the most important variables of destination competitiveness; and the inability to rank the most competitive destinations, since the comparisons made considered only the attributes of the studied destination in relation to others (Taberner, 2007). Finally, the model considers only demand information, ignoring aspects of the tourist offer (Castrillón et al., 2011).

Other specific studies also bring important contributions to destination competitiveness debate. Hassan (2000) proposes a model for evaluating the competitiveness of tourist destinations focusing on sustainability. According to the author, there is a connection between these two constructs, because destination attractiveness depends on the uniqueness of its environment. Buhalis (2000) emphasizes the role of marketing and the market positioning for tourist destinations. Both Hassan (2000) and Buhalis (2000) point out that tourism destinations have lifecycles and that the factors considered as competitiveness determinants may change as destinations evolve and become more mature (Hassan, 2000; Buhalis, 2000; Croes, 2011).

Considering that prices are decisive for destination competitiveness, Dwyer, Forsythe, and Rao (2000) examine the price competitiveness of nineteen international tourist destinations (countries). An index of price competitiveness is proposed in which two price categories are analyzed: prices related to the trip (travel costs), and prices related to goods and services in the destination (local costs). The study main contribution was the application of a method for the construction of competitiveness indicators based on prices. This method allows direct comparison between destinations taking into account specific purchase patterns (Dwyer et al., 2000). Croes (2011) criticizes this type of model based on prices. Given the nature of the tourism product-based on the visitors’ experience-comparisons based solely on price loses informative value (Croes, 2011). Additionally, the positive and/or negative tourism potential impacts on local development are not considered.

Also starting from a systemic perspective (Domareski-Ruiz, Akel & Gândara, 2015), Dwyer and Kim (2003) proposed a destination competitiveness model with several variables initially identified by Crouch and Ritchie (1999). Dwyer and Kim’s (2003) model, however, advances the discussion by establishing a clearer relationship between competitiveness dimensions and identifying those that would have a direct or indirect influence on competitiveness. In addition, they proposed a set of possible indicators for the model variables, which represents a step forward in relation to one of the Crouch and Ritchie’s (1999) model limitations. According to Dwyer and Kim (2003), destination competitiveness is an intermediate goal towards socioeconomic prosperity. Despite presenting a set of variables for competitiveness assessment, Dwyer and Kim’s (2003) model still remain difficult to apply due to the absence of comparable information on the different destinations (Domareski-Ruiz, Akel & Gândara, 2015).

Considering tourism as an alternative to employment and income generation, Heath (2003) proposes a conceptual model for assessing competitiveness in the South African subcontinent. Heath’s (2003) model considers destination competitiveness as a house whose foundations are composed of key attractions (created or native); non-negotiable aspects; enabling elements; elements that add value; facilitating elements; and, elements that enhance the experience. The walls of the hypothetical house would be made of sustainable development policies and destination marketing and promotion strategy. Such groups of aspects must be interconnected by channels of interaction and communication between organizations involved in the destination management. The roof of the house would be a shared strategic vision that could allow different actors to play their roles properly (Heath, 2003). Heath’s (2003) model converges on several aspects with those of Crouch and Ritchie (1999) and Dwyer and Kim (2003). Despite organizing and establishing a relationship between variables, Heath (2003) does not establish indicators to evaluate destination competitiveness.

Gooroochurn and Sugiyarto (2004) propose a quantitative methodology to measure and evaluate the countries’ competitiveness through databases available in international organizations. The Competitiveness Monitor (Gooroochurn & Sugiyarto, 2004) establishes a competitiveness index that allows comparisons and ranking countries competitiveness. The use of international organization databases overcomes the lack of data about the industry (Taberner, 2007), a limitation also common to the previous models. Yet the Competitiveness Monitor’s limitations include the excessive weight attributed to the variables related to technology and the secondary role played by environmental variables (Taberner, 2007; Castrillón et al., 2011). Taberner (2007) also points out that the Competitiveness Monitor’s results have a limited relation with the reality because the countries identified as the most competitive are not amongst the main tourist destinations worldwide.

Taberner (2007) proposes a model to evaluate tourism competitiveness composed of two indexes: (i) demand competitiveness; and (ii) competitiveness of the available resources. The first one is calculated from tourist opinions about destination attractive factors and the quality of the services consumed using a survey. This evaluation presents the consumer perspective on the necessary attributes to satisfy their motivations when visiting a certain destination. The competitiveness index of the available resources, in turn, is subdivided into two indicators: the economic competitiveness and the tourism sector competitiveness. Taberner (2007) recognizes that tourism competitiveness is directly related to economic competitiveness. Regarding the tourism sector competitiveness, Taberner (2007) identifies important factors from the supply perspective. Taberner’s (2007) model does not consider important variables identified in other models such as: Cooperation between destination organizations, destination management, and environmental management. The WEF measures the countries tourism competitiveness through the Travel and Tourism Competitiveness Report. The proposed model has three broad categories related to the travel and tourism sector - Regulatory Framework; Business Environment and Infrastructure; and Human, Natural and Cultural Resources-which are subdivided into 14 subcategories. Indexes and index components are based on indicators and quantitative information collected from international organizations, as well as qualitative surveys conducted with leading companies in the sector (WEF, 2015). The Travel and Tourism Competitiveness Report was developed for application at the national level and, given the set of information employed, it is difficult to apply to municipalities or destinations (Crouch, 2011). Tourism is a locally based economic activity and a country-level analysis fails to distinguish local and regional realities (Rodrigues & Carrasqueira, 2011).

In order to guide public policies for tourism development, the Brazilian Ministry of Tourism (MTur), in partnership with the Support Agency for Micro and Small Businesses (SEBRAE) and Getulio Vargas Foundation (FGV), developed a model to evaluate the competitiveness of 65 Brazilian tourist destinations. The Brazilian Model evaluates the destination competitiveness from an index composed of five macro dimensions and thirteen dimensions (MTur, SEBRAE & FGV, 2013). The Brazilian Model was conceived, organized, and structured with a focus on the reality of the Brazilian municipalities in a customized perspective (Domareski-Ruiz, Akel & Gândara, 2015).

The Brazilian model solves some of previous models’ limitations such as the applicability to the destinations, the use of measurable indicators, and comparability. Yet the study encompasses destinations competing in different segments. As Rivero and Caldera (2004) point out, there is no set of indicators that can be unrestrictedly applied to all tourist destinations. Depending on the characteristics of the destination evaluated some indicators would be more or less relevant (Rivero & Caldera, 2004; Cvelbar et al., 2016; Sette, Santos & Uvinha, 2017). Other criticisms indicate the narrow focus on the internal aspects of the destination and the absence of external information such as demand information (Sette & Tomazzoni, 2017).

Despite the lack of consensus on the concept of competitiveness and the difficulties in its measurement (Añaña, Pereira & dos Anjos, 2015; Domareski-Ruiz, Akel & Gândara, 2015; Sette & Tomazzoni, 2017; Sette; Santos & Uvinha, 2017), Crouch (2011) argues that the models for destination competitiveness evaluation reached a maturity in which the characteristics that influence competitiveness are mapped, without, however, identifying which aspects are determinant. Cvelbar et al. (2016) present evidence that responds to the questioning proposed, when analyzing the competitiveness of 139 countries from six variables divided into two major groups: (i) indicators associated with destination resources as: endowed resources, destination management, and tourism infrastructure; and (ii) indicators associated with the general economic characteristics like: business environment, macro environment, and general infrastructure. The analysis showed that the determinants of destination competitiveness vary according to the country development stage, which means that the most important variables for developing countries are different from those for developed countries (Cvelbar et al., 2016). Despite the evidence provided, Crouch’s (2011) inquiry remains unanswered at a destination level of analysis.

3 METHOD

This study is characterized as a descriptive research. The universe comprises 27 sun and sand destinations selected by the MTur as inductors of national tourism. The choice for a specific segment is due to the need of a comparison, inherent to the determination of competitiveness. Destinations are presented in Frame 1.

Frame 1
Geographical Distribution of the Destinations Analyzed

Region	Cities
Northeast	Aracaju; Aracati; Fernando de Noronha; Fortaleza; Ipojuca; Jijoca de Jericoacoara; João Pessoa; Lençóis; Maceió; Maragogi; Marau; Mata de São João; Natal; Parnaíba; Porto Seguro; Recife; Salvador; São Luís; Tibau do Sul.
South	Balneário Camboriú; Florianópolis
Southeast	Angra dos Reis; Armação dos Búzios; Ilhabela; Paraty; Rio de Janeiro; Vitória.

Analyzes were performed from secondary data. Data on competitiveness were gathered from the Brazilian Competitiveness Model (MTur, SEBRAE & FGV, 2013). The Brazilian Models evaluates destination competitiveness from 13 dimensions: General Infrastructure (Infr); Access (Acce); Tourism Services and Equipment (Serv); Tourist Attractions (Attr); Marketing (Mrkt); Public Policy (PPol); Regional Cooperation (Coop); Monitoring (Mont); Local Economy (Econ); Business Capabilities (BusC); Social Aspects (SocA); Environmental Aspects (EnvA); and Cultural Aspects (Cult). The Brazilian Competitiveness Model was effectively applied between the years 2008 to 2015 (except for 2012). Specifically, for the purposes of this article, we use the year 2013 information.

We evaluate destination performance based on data from the number of domestic and international visitors. As highlighted by Coelho (2015), the concepts of attractiveness and competitiveness are related. In both cases, its materialization occurs from the displacement of visitors to a place of interest or a destination. The number of visitors, as well as its growth rate are identified by Dwyer and Kim (2003) as indicators associated with destination competitiveness. Data on the number of domestic and international tourists were collected from National and International demand studies performed by the Brazilian Ministry of Tourism in the years 2012 and 2013 respectively (MTur, 2012; 2013). It is worth noticing that the profiles of domestic and international tourists are quite distinct. According to the International Demand Study (MTur, 2013), international tourists’ main motivation is leisure and the sun and sand tourism is the main reason for traveling (65.9%). The average daily per capita expenditure of international leisure tourists is US$68.55 and average length of stay is 12.6 days. The Domestic Demand Survey (MTur, 2012) does not present information on the percentage of leisure tourists in relation to other travel reasons, however daily per capita expenditure of the domestic tourist is approximately US$28.5 in leisure travel and US$44.2 in business trips. The average length of stay is 8.7 and 11.2 days respectively. Domestic tourist presents a regionalized travel pattern, often traveling within the state of residence (MTur, 2012). In this sense, state capitals play an important role, either as a gateway to state destinations or as a pole of attraction for leisure or business tourists. For both domestic and international demand, it was not possible to obtain specific information on the number of tourists by leisure motivation, which would provide a more accurate comparison amongst sun and sand destinations. We acknowledge this as a limitation of the study.

Qualitative Comparative Analysis (QCA) was used as the analysis technique. This method allows the use of an intermediate number of cases, which are neither sufficiently large for traditional quantitative approaches nor too small to produce representative conclusions (Ragin, 1987; Ragin, Shulman, Weinberg, & Gran, 2003). QCA may also be considered a quantitative analysis since it is based on the observation of varying conditions through different elements. These conditions are analyzed using mathematical techniques (although not statistics) based on tools such as Set Theory or Boolean algebra (Medina, Ortiz, Álamos-Concha, & Rioux, 2017).

The QCA is usually defined as an analysis technique appropriate for small or intermediate-sized samples, usually with a minimum of 10 to a maximum of 50 cases (Gerring, 2012). Thus, it allows the analysis of a broader set of cases than traditional qualitative techniques, such as the case study method (Wagemann, 2012). Although still with incipient application in Latin America (Wagemann, 2012) and in Brazil (Betarelli Junior, & Ferreira, 2018), considering the difficulty of obtaining comparable information for a large sample of destinations in order to analyze competitiveness (Domareski-Ruiz, Akel and Gândara, 2015), the QCA may be a research technique suitable to overcome this limitation.

The QCA is a method used for the treatment of complex sets of binary data, with the aid of Boolean algebra. Its objective is to establish logical relations between causal conditions (in our case the competitiveness dimensions) and an outcome variable (for the purpose of this paper domestic and international demand). Both causal conditions and outcome variables must be expressed in dichotomous terms, where 1 (one) symbolizes the presence of the attribute/indicator in question and 0 (zero) the absence.

For the dichotomization process, we followed the guidelines proposed by Rioux and De Meur (2009). The authors explain that to dichotomize conditions in a meaningful way, as a resort, some more mechanical cut off points such as the mean or median can be used. According to Levin and Fox (2004), the mean is strongly influenced by extreme scores, however, the median suffers little or no change in the presence of outliers. Considering the large variance among the cases, especially in the outcome variables, the median score was used as the reference value for the dichotomization of both competitiveness and demand variables. The median is a position measure that separates the higher half from the lower half of a data sample. For each of the variables, the cases were ordered in descending order and the cases with values ​​above the median value were classified as with the presence (value 1) of the variable, while all others were marked with the absence of the variable (value 0).

The original QCA version is the so-called crisp-set QCA (csQCA), that is, analysis of clear sets, a method that shows a set of specific combinations of causal conditions, which are examined in relations between sets. The QCA analysis identifies which variables are sufficient and/or necessary conditions for a given result by means of logical equations. The comparative analysis takes into account logical and non-arithmetic principles, through multiplication and addition operations in a combinational logic. The present research used the Tosmana program (Tool for Small N Analysis) and followed the recommended steps by Rihoux and De Meur (2009).

Provided that domestic and international demand are different segments, the performance variables were analyzed separately. The 13 competitiveness dimensions were considered together in the analyses. In this sense, the QCA analysis sought to discern situations that configured sufficient and/or necessary conditions for domestic and international performance. The procedure was performed through the complete logic equation and then the minimized equation, as recommended by Rihoux and De Meur (2009). The next sections present the results achieved.

4 RESULTS AND ANALYSIS

The dichotomization of the performance variables (Tables 1 and 2) resulted in 18 destinations with good performance and 9 destinations with poor performance for both international and domestic criteria variables. Three of the destinations achieved a good performance in the international demand, but did not obtain the same result for the domestic demand-J. de Jericoacoara, Mata de São João, and Tibau do Sul. Three other destinations were successful in the domestic performance, but they obtained a diverse result in the international demand-Aracaju, Ipojuca, and Parnaíba.

Table 1
Dichotomization of Destination Variables - Domestic Performance

Destination	Infr	Acce	Serv	Attr	Mrkt	PPol	Coop	Mont	Econ	BusC	SocA	EnvA	Cult	Perf.
Angra dos Reis	0	1	0	0	1	1	0	1	1	1	0	1	1	1
Aracati; Parnaíba; Tibau do Sul	0	0	0	0	0	0	0	0	0	0	0	0	0	C
A.dos Búzios	0	0	0	0	0	1	0	0	1	0	0	1	0	1
B.Camboriú	0	1	1	1	1	1	1	1	0	0	1	1	1	1
F.Noronha	1	0	0	1	1	0	0	0	0	0	1	0	0	0
Ilhabela	1	0	1	0	0	1	1	1	0	0	1	1	0	0
Ipojuca	0	0	0	1	0	0	0	0	1	0	0	0	0	1
J.Jericoacoara	0	0	0	0	1	0	1	0	0	0	1	0	0	0
Lençóis	1	0	0	1	0	0	1	1	0	0	0	0	0	0
Maragogi	0	0	0	1	0	0	1	0	0	0	0	0	0	0
Marau	0	0	0	0	0	0	1	0	0	0	0	0	0	0
Mata de S. Joao	0	0	0	1	1	0	0	0	0	0	1	1	0	0
Paraty	0	0	0	1	0	0	0	0	0	0	0	0	1	1
Porto Seguro	0	1	1	0	0	1	0	0	0	1	0	1	0	1
Aracaju	1	1	0	0	1	0	1	0	0	1	0	0	1	1
Florianópolis	1	1	1	1	1	1	1	1	1	1	1	1	1	1
Rio de Janeiro	1	1	1	1	1	1	1	1	1	1	1	1	1	1
Fortaleza	1	1	1	1	0	1	1	1	1	1	1	1	1	1
Joao Pessoa	1	1	1	0	1	1	0	1	1	1	1	0	1	1
Maceió	0	1	1	0	0	1	1	1	1	1	0	1	1	1
Natal	1	1	1	0	0	0	1	0	1	1	0	1	0	1
Recife; Salvador	1	1	1	1	1	1	0	1	1	1	1	1	1	1
São Luís	1	0	1	0	1	0	0	1	1	1	1	0	1	1
Vitória	1	1	1	1	1	1	1	1	1	1	1	0	1	1

• Legend: 0 - absent variable; 1 - present variable; C - contradictory result.

Table 2
Dichotomization of Destination Variables - International Performance

Destination	Infr	Acce	Serv	Attr	Mrkt	PPol	Coop	Mont	Econ	BusC	SocA	EnvA	Cult	Perf.
Angra dos Reis	0	1	0	0	1	1	0	1	1	1	0	1	1	1
Aracati; Parnaíba; Tibau do Sul	0	0	0	0	0	0	0	0	0	0	0	0	0	C
A.dos Búzios	0	0	0	0	0	1	0	0	1	0	0	1	0	1
B.Camboriú	0	1	1	1	1	1	1	1	0	0	1	1	1	1
F.Noronha	1	0	0	1	1	0	0	0	0	0	1	0	0	0
Ilhabela	1	0	1	0	0	1	1	1	0	0	1	1	0	0
Ipojuca	0	0	0	1	0	0	0	0	1	0	0	0	0	0
J.Jericoacoara	0	0	0	0	1	0	1	0	0	0	1	0	0	1
Lençóis	1	0	0	1	0	0	1	1	0	0	0	0	0	0
Maragogi	0	0	0	1	0	0	1	0	0	0	0	0	0	0
Marau	0	0	0	0	0	0	1	0	0	0	0	0	0	0
Mata S.Joao	0	0	0	1	1	0	0	0	0	0	1	1	0	1
Paraty	0	0	0	1	0	0	0	0	0	0	0	0	1	1
Porto Seguro	0	1	1	0	0	1	0	0	0	1	0	1	0	1
Aracaju	1	1	0	0	1	0	1	0	0	1	0	0	1	0
Florianópolis	1	1	1	1	1	1	1	1	1	1	1	1	1	1
Rio de Janeiro	1	1	1	1	1	1	1	1	1	1	1	1	1	1
Fortaleza	1	1	1	1	0	1	1	1	1	1	1	1	1	1
Joao Pessoa	1	1	1	0	1	1	0	1	1	1	1	0	1	1
Maceió	0	1	1	0	0	1	1	1	1	1	0	1	1	1
Natal	1	1	1	0	0	0	1	0	1	1	0	1	0	1
Recife; Salvador	1	1	1	1	1	1	0	1	1	1	1	1	1	1
São Luís	1	0	1	0	1	0	0	1	1	1	1	0	1	1
Vitória	1	1	1	1	1	1	1	1	1	1	1	0	1	1

• Legend: 0 - absent variable; 1 - present variable; C - contradictory result.

4.1 Domestic Demand

One might observe that destinations with the presence of more than four dimensions usually reached a successful outcome in terms of domestic demand. Some exceptions are Ilha Bela, which did not perform well despite the presence of seven dimensions. Whereas Armação de Búzios was successful with the presence of three dimensions (Public Policy, Local Economy, and Environmental Aspects). Two cases were successful with the presence of only two variables: Ipojuca (with the presence of Tourist Attractions and Local Economy) and Paraty (with the presence of Tourist Attraction and Cultural Aspects). Three cases (Aracati, Parnaíba, Tibau do Sul) presented absence in all thirteen dimensions and obtained contradictory results. That is, they represent cases with both good and poor performance, even without presenting any of the variables with high levels (presence) of punctuation. Table 3 summarizes the 14 combinations resulted from the cases analyzed.

Table 3
General Equation with Dimensions Competitiveness for Domestic Performance

	Infr	Acce	Serv	Attr	Mrkt	PPol	Coop	Mont	Econ	BusC	SocA	EnvA	Cult
Comb.1	1	1	1	1	N	1	1	1	1	1	1	1	1
Comb.2	1	1	1	1	1	1	N	1	1	1	1	1	1
Comb.3	1	1	1	1	1	1	1	1	1	1	1	N	1
Comb.4	0	1	0	0	1	1	0	1	1	1	0	1	1
Comb.5	0	0	0	0	0	1	0	0	1	0	0	1	0
Comb.6	0	1	1	1	1	1	1	1	0	0	1	1	1
Comb.7	0	0	0	1	0	0	0	0	1	0	0	0	0
Comb.8	0	0	0	1	0	0	0	0	0	0	0	0	1
Comb.9	0	1	1	0	0	1	0	0	0	1	0	1	0
Comb.10	1	1	0	0	1	0	1	0	0	1	0	0	1
Comb.11	1	1	1	0	1	1	0	1	1	1	1	0	1
Comb.12	0	1	1	0	0	1	1	1	1	1	0	1	1
Comb.13	1	1	1	0	0	0	1	0	1	1	0	1	0
Comb.14	1	0	1	0	1	0	0	1	1	1	1	0	1
% Cases	50.0	71.4	64.3	42.9	50.0	64.3	42.9	57.1	71.4	71.4	42.9	57.1	71.4

• Legend: 0 - Variable Absent; 1 - Variable Present; N - Variable is not a condition for the logical operation.

Our results evidence that to achieve a higher performance it is not necessary a large number of dimensions highly developed. It is sufficient to have the presence of specific variables to influence the outcome expected. According to Rihoux and De Meur (2009), there are unnecessary conditions that can be removed from the complete initial expression, resulting in a shorter expression (called a prime implicant). Thus, with the help of the Tosmana program, the option of excluding the logical fragments and the contradictions were selected, using the parsimony principle, to arrive at the two reduced expressions:

$\begin{array}{l}Access\left\{1\right\}+LocalEconomy\left\{1\right\}+CulturalAspects\left\{1\right\};\hfill \\ \hfill \\ LocalEconomy\left\{1\right\}+BusinessCapabilities\left\{1\right\}+CulturalAspects\left\{1\right\}.\hfill \end{array}$

The logical minimization resulted in two equations that cover all successful cases. From the shorter expression, it is evident that there was a reduction in the set of specific combinations that result in positive performance. Nevertheless, the result indicates four determinants for success in domestic demand: Access, Cultural Aspects, Local Economy, and Business Capabilities. The first two are observed in both equations. All conditions are sufficient, but not necessary for the outcome. Results indicate that to achieve the higher performance in domestic demand it is enough to develop one of these dimensions.

Taberner (2007) states that tourism is an easily marketed product, albeit of intense competition. Despite this argument, results suggest that, when it comes to domestic demand, competition does not take place through a complex structure, which evaluation models are trying to capture (Crouch, 2011), but on some particular aspects, which brings the topic closer to Barney’s (1991) resource-based view arguments about the role of strategical resources providing competitive advantage. As it was argued, domestic demand presents a regionalized travel pattern, which may explain the competitiveness complexity reduction and the positive influence of specific aspects for the inflow of domestic tourists.

Ritchie and Crouch (2010) classify resources as support and core resources and attractions. Similarly, Dwyer and Kim (2003) classify the destination resources into three categories: innate, created, and support. Innate resources are the basis from which tourism products, especially those linked to leisure tourism, are created. The other two operate as assets created to explore the innate resources. Access infrastructure, as other general or tourism infrastructure, is classified as a support resource. Although infrastructure is not an aspect capable of inducing demand, it is identified by several authors as a created resource that enables tourism development (Crouch & Ritchie, 1999; Dwyer & Kim, 2003; Gooroochurn & Sugiyarto, 2004; Heath, 2003; Ritchie & Crouch, 2010). Cvelbar et al. (2016) highlighted the importance of the infrastructure for the competitiveness of both developed and developing destinations, being even more important for the second group. Our results point out the differential role played by the access infrastructure for domestic demand performance. Crouch and Ritchie (1999) point out that an attraction can only be explored as tourism if it can be accessed by visitors. Thus, although different types of infrastructure are necessary, access infrastructure stands out for its direct relation to destination performance in terms of facilitating demand.

Following Dwyer and Kim (2003) classification, Cultural Aspects are destination innate resources that must be properly exploited for the success of the tourist activity. Cultural aspects, together with natural resources, are part of the central attractions of a destination (Crouch & Ritchie, 1999; Ritchie & Crouch, 2010), and influence demand (Bornhorst et al., 2010). Considering that all the destinations analyzed operate in the Sun and Sand segment, the presence of Cultural Aspects complements the main attractions and enhances the experience offered (Buhalis, 2000; Dwyer & Kim, 2003). Thus, Cultural Aspects may impact the quality of the experience provided, contribute to a better market positioning (Hassan, 2000) and, consequently, increase destination performance (Bornhorst et al., 2010). As argued by Coelho (2015) the diversity of products and services is paramount for tourism development.

Besides destination resources, the competitive environment also influences destination performance (Dwyer & Kim, 2003; Ritchie & Crouch, 2010). Local Economy and Business Capabilities are support factors that enable the exploration of endowed resources (Crouch & Ritchie, 1999). Companies vitality and their ability to invest, innovate and diversify their production are directly related to destination economic prosperity and, consequently, to the destination competitiveness (Crouch & Ritchie, 1999; Ritchie & Crouch, 2010). Dwyer and Kim (2003) characterize Local Economy and Business Capabilities as competitive microenvironment and emphasize the importance of companies in adapting and exploiting the opportunities for the development of the destination. The findings corroborate those of Cvelbar et al. (2016), even though our results indicate the relevance of business environment dimensions for both developing and developed destinations. Considering our findings, it is possible to notice that both internal and environmental resources influence destination performance, which reinforces the idea that destination competitiveness is a multilevel phenomenon (Bornhorst et al., 2010).

4.2 International Demand

The same standards applied earlier for domestic performance were used for international performance analysis. There are 14 sets of combinations that explain the presence of the criteria variable (Table 4). International performance was achieved with the presence of more than four competitiveness dimensions. As shown in Table 2, Florianopolis and Rio de Janeiro achieved international performance with the presence of all 13 dimensions. The exception, however, can be found in six cases. Ilha Bela (presence of 7 dimensions) and Aracaju (presence of 6 dimensions) were not successful. Armação de Búzios, with 3 dimensions (Public Policy, Local Economy, and Environmental Aspects); Jijoca de Jericoacoara, with 3 dimensions (Marketing, Regional Cooperation, and Social Aspects); Mata de São João with 4 dimensions (Tourist Attractions, Marketing, Social Aspects, and Environmental Aspects); and Paraty, with 2 dimensions (Tourist Attractions and Cultural Aspects) reached a successful result even with the presence of a reduced number of dimensions.

Table 4
General Equation with Competitiveness Dimensions for International Performance

	Infr	Acce	Serv	Attr	Mrkt	PPol	Coop	Mont	Econ	BusC	SocA	EnvA	Cult
Comb.1	1	1	1	1	N	1	1	1	1	1	1	1	1
Comb.2	1	1	1	1	1	1	N	1	1	1	1	1	1
Comb.3	1	1	1	1	1	1	1	1	1	1	1	N	1
Comb.4	0	1	0	N	1	1	0	1	1	1	0	1	1
Comb.5	0	0	0	0	0	1	0	0	1	0	0	1	0
Comb.6	0	1	1	1	1	1	1	1	0	0	1	1	1
Comb.7	0	0	0	0	1	0	1	0	0	0	1	0	0
Comb.8	0	0	0	1	1	0	0	0	0	0	1	1	0
Comb.9	0	0	0	1	0	0	0	0	0	0	0	0	1
Comb.10	0	1	1	0	0	1	0	0	0	1	0	1	0
Comb.11	1	1	1	0	1	1	0	1	1	1	1	0	1
Comb.12	0	1	1	0	0	1	1	1	1	1	0	1	1
Comb.13	1	1	1	0	0	0	1	0	1	1	0	1	0
Comb.14	1	0	1	0	1	0	0	1	1	1	1	0	1
% Cases	42.9	64.3	64.3	42.9	57.1	64.3	42.9	57.1	64.3	64.3	57.1	64.3	64.3

• Legend: 0 - variable absent; 1 - variable present; N - variable is not a condition on the logical operation.

We reduced the unessential conditions by minimizing the general equation, as done previously. The result, however, generated a large number of alternative equations to represent the combinations of both poor and high performances so that the minimized equation was not achieved. Nevertheless, the analysis of the data in Table 4 makes it possible to argue that none of the competitiveness dimensions analyzed is a necessary condition (not a single dimension was found present in all equations) or sufficient (no dimension alone explains the criteria variable) to justify a good performance in international demand. Additionally, no dimension can be considered superfluous to explain performance. Even so, we might observe that some dimensions occur more frequently, like: Access, Tourism Services and Equipment, Public Policy, Local Economy, Business Capabilities, Environmental Aspects, and Cultural Aspects.

The dimensions Access, Cultural Aspects, Local Economy, and Business Capabilities already appeared as important aspects when considering domestic demand. The repeated presence of these dimensions in the equations of international demand corroborates the initial results and reinforces their relevance for destination performance. The dimensions Tourism Services and Equipment and Public Policy, although they appear with a similar frequency for the domestic demand, they were not previously identified with the same importance.

The Services and Equipment dimension considers the existing tourism structure and private services offered to tourists (MTur, SEBRAE & FGV, 2013). Services and equipment add value to endowed resources and contribute to sustain and enhance the destination competitive position (Hassan, 2000). A destination cannot rely solely on their natural attractions since destination competitiveness relates to the ability to provide visitors with high quality products and services (Croes, 2011).

Even though transportation, general infrastructure, and several other public goods associated with tourism are usually provided by Governments, tourism public policies apparently play a secondary role in destination competitiveness models. Eventually, this diminished role is due to the characteristics of the tourism economy in developed destinations that inspired the main destination competitiveness models. However, in Brazil, local Governments are usually directly involved in the management and planning of tourist destinations, aspects usually associated with destination management (Crouch & Ritchie, 2010; Dwyer & Kim, 2003). Our result reinforces this aspect, provided that the Public Policy dimension repeatedly appears among successful combinations for international demand. Cvelbar et al. (2016) identified destination management as the main driver of destination competitiveness. It is interesting to notice that this dimension emerges as a differential in international demand. This type of demand is usually more qualified in terms of the economic impact generated. In this sense, one may argue that Public Policy creates a favorable environment for tourism development and local development (Heath, 2003).

Environmental Aspects (like Cultural Aspects) are destinations’ innate resources (Dwyer & Kim, 2003) composing the set of resources and central attractions of a destination (Crouch & Ritchie, 1999; Ritchie & Crouch, 2010). The presence of these dimensions together is in line with the World Economic Forum (2015) findings that indicate cultural and natural resources as the dimensions in which Brazil was better evaluated. Natural and cultural attractions, however, are related to the comparative advantage of destinations. These resources ought to be properly deployed to achieve competitive advantage (Crouch & Ritchie, 1999). Hassan (2000) points out that destinations should exploit their unique comparative advantages to be appealing to a particular market segment. Destination competitiveness relates to how efficiently and effectively these resources are explored in order to enhance local population welfare (Ritchie & Crouch, 2010).

5 CONCLUSIONS, LIMITATIONS, AND RECOMMENDATIONS

In this paper, we identify the competitiveness dimensions that are determinant for the performance of 27 Brazilian sun and sand destinations. Destination performance was evaluated by both domestic and international demand. Data on destination competitiveness was obtained from the Brazilian Competitiveness Model (MTur, SEBRAE & FGV, 2013). The data were analyzed using the QCA technique. The results highlight the importance of Access, Cultural Aspects, Local Economy, and Business Capabilities for destination performance on both domestic and international demand. Considering the international demand, besides these dimensions, the results stress the relevance of Services and Equipment, Public Policy, and Environmental Aspects. Despite a partial convergence, international demand is apparently more complex than domestic demand. These results are consistent with previous evidence about country tourism competitiveness provided by Cvelbar et al. (2016) and present a possible answer to the inquiry proposed by Crouch (2011) about the determinant attributes for the competitiveness of sun and sand destinations.

Destination competitiveness models were developed in a multilevel perspective considering the heterogeneity of the resources available at destinations. These models were able to provide an acceptable explanation of how a destination become competitive. Regardless, from the outcomes found for both for domestic and international demand, we conclude that it is not necessary to have a high level of development in a large number of competitiveness dimensions in order to achieve a high performance. This reinforces the perspective that competitiveness, even for destinations acting in the same market segment, is multidimensional (Crouch & Ritchie, 1999), since different destination aspects might result in good performances. In this sense complex and comprehensive destination competitiveness models may not provide adequate guidance for destination development without further analysis. Eventually, the research field should evolve towards more parsimonious models dedicated to specific tourist segments in order to provide clearer directions for both theory and practice.

From a destination management perspective, considering resource-based view arguments (Barney, 1991), instead of trying to improve several aspects simultaneously, eventually, sun and sand destinations ought to focus on those attributes that already constitute differentials in order to assure a market positioning. This requires knowledge about the resources available in the destination and in its competitors, as well as the characteristics of the current and intended demand, which reinforces the role of destination management in market monitoring. Proximity to emitting markets and ease of access seem to be central aspects for domestic flows, however, to attract more qualified demand (such as international demand), one must also consider the possibility of complementing tourism attractions with other local characteristics (cultural or other natural attractions). Considering tourism is an economic activity exploited by private initiative, it is also worth mentioning the entrepreneurial capacity to innovate and effectively explore the innate characteristics present in the destination.

Our evaluation considered only ex-post indicators focusing exclusively on the inflow of domestic and international visitors for performance evaluation, which might be considered a limitation, since destination competitiveness is only an intermediate goal towards social and economic development (Crouch & Ritchie, 1999; Dwyer & Kim, 2003; Heath, 2003; Rivero & Caldera, 2004). Considering international demand, it was not possible to produce a minimized equation, which might be considered another limitation. Similarly, the analysis technique does not inform if the dependent variable increases or decreases according to the variation of the independent variable, in a direct relation or how much it interacts with the other affecting variables.

The proposed analytical approach makes it possible to model the logical relations between the variables on sufficiency, need or some specific conditions, such as when the variable (condition) is sufficient, but not necessary in itself to explain the outcome or an inverse condition. As a suggestion for future research, one can expand the scope with the employment of other analytical techniques. The refinement of the measurement would make it possible to use of comparative qualitative fuzzy analysis (fuzzy-set QCA). In addition, longitudinal studies may evidence how the determinant aspects of destination competitiveness evolve as destinations mature or as market demands change over time.

REFERENCES

• Añaña, E. S., Pereira, M. L., & Anjos, F. A. (2015) Competitividade de Destinos Turísticos na Visão da Demanda: introdução de um novo método de avaliação. Revista Turismo em Análise, 26(4). DOI:https://doi.org/10.11606/issn.1984-4867.v26i4p859-879
  » https://doi.org/10.11606/issn.1984-4867.v26i4p859-879
• Barney, J. B. (1991). Firm Resources and Sustained Competitive Advantage. Journal of Management, 17(1), pp. 99-120. DOI: https://doi.org/10.1177/014920639101700108
  » https://doi.org/10.1177/014920639101700108
• Betarelli Junior, A. A., & Ferreira, S. F. (2018). Introdução à análise qualitativa comparativa e aos conjuntos Fuzzy (fsQCA). Brasília. Enap.
• Buhalis, D. (2000). Marketing the competitive destination of the future. Tourism Management, 21, pp. 97 - 116. DOI: https://doi.org/10.1016/S0261-5177(99)00095-3
  » https://doi.org/10.1016/S0261-5177(99)00095-3
• Bornhorst, T., Ritchie, J.R.B. & Sheehan, L. (2010). Determinants of tourism success for DMOs & destinations: An empirical examination of stakeholders’ perspectives. Tourism Management, 31, pp. 572-589. DOI: https://doi.org/10.1016/j.tourman.2009.06.008
  » https://doi.org/10.1016/j.tourman.2009.06.008
• Carmona, V. C., Costa, B. K., & Ribeiro, H. C. M. (2014). Competitividade e Turismo: estudo da produção científica internacional. Revista Brasileira de Pesquisa em Turismo, 8(2), pp. 201-221. DOI: https://doi.org/10.7784/rbtur.v8i2.721
  » https://doi.org/10.7784/rbtur.v8i2.721
• Castrillón, I. D., Canto, A. G., Cantorna, A. S. & Cerradelo, L. B. (2011). Analysis of the main explanatory destination competitiveness models in the framework of sustainability. Revista Cultura y Turismo, 5(2).
• Camisón, C., & Forés, B. (2015). Is tourism firm competitiveness driven by different internal or external specific factors? New empirical evidence from Spain. Tourism Management, 48, pp. 477-499. DOI https://doi.org/10.1016/j.tourman.2015.01.001
  » https://doi.org/10.1016/j.tourman.2015.01.001
• Costa, H.A., & Hoffmann, V. E. (2006). Competitiveness in Tourist Destinations: elements and indicators applied to a study of tourism management in Balneário Camboriú-SC, Brazil. Turismo em Análise, 17 (2), p. 135-154. DOI: https://doi.org/10.11606/issn.1984-4867.v17i2p135-154
  » https://doi.org/10.11606/issn.1984-4867.v17i2p135-154
• Coelho, M. F. (2015) O que Atrai o Turista? Gestão da Competitividade de Destinos a Partir de Atrações e da Atratividade Turística. Rosa dos Ventos - Turismo e Hospitalidade, 7(4), pp. 489-505. DOI: https://doi.org/10.18226/21789061.v7iss4p489
  » https://doi.org/10.18226/21789061.v7iss4p489
• Croes, R. (2011). Measuring and Explaining Competitiveness in the Context of Small Island Destinations. Journal of Travel Research, 50(4): 431-442. DOI: https://doi.org/10.1177/0047287510368139.
  » https://doi.org/10.1177/0047287510368139.
• Crouch, G. I. (2011). Destination Competitiveness: An Analysis of Determinant Attributes. Journal of Travel Research, 50(1), pp. 27 -45. DOI: https://doi.org/10.1177/0047287510362776
  » https://doi.org/10.1177/0047287510362776
• Crouch, G. I., & Ritchie, J. R. B. (1999). Tourism, Competitiveness, and Societal Prosperity. Journal of Business Research, 44(3), pp. 137-152. DOI: https://doi.org/10.1016/S0148-2963(97)00196-3
  » https://doi.org/10.1016/S0148-2963(97)00196-3
• Cvelbar, L. K., Dwyer, L., Koman, M., & Mihalic, T. (2016). Drivers of Destination Competitiveness in Tourism: a Global Investigation. Journal of Travel Research, 55(8). DOI: https://doi.org/10.1177/0047287515617299
  » https://doi.org/10.1177/0047287515617299
• Domareski-Ruiz, T. C., Akel, G. M., & Gândara, J. M. G. (2015) Estudos de Competitividade Turística - Comparativo do Modelo de Dwyer e Kim e do Estudo de Competitividade dos 65 Destinos Indutores do Brasil. Turismo e Sociedade, 8(1). DOI: https://doi.org/10.5380/tes.v8i1.34299
  » https://doi.org/10.5380/tes.v8i1.34299
• Dwyer, L., & Kim, C. (2003). Destination competitiveness: determinants and indicators. Current Issues in Tourism, 6(5). DOI: https://doi.org/10.1080/13683500308667962
  » https://doi.org/10.1080/13683500308667962
• Dwyer, L., Forsyth, P., & Rao, P. (2000). The price competitiveness of travel and tourism: a comparison of 19 destinations. Tourism Management, 21, pp. 9-22. DOI: https://doi.org/10.1016/S0261-5177(99)00081-3
  » https://doi.org/10.1016/S0261-5177(99)00081-3
• Gerring, J. (2012). Social Science Methodology: A Unified Framework. Cambridge University Press.
• Gooroochurn, N. & Sugiyarto, N. (2004). Measuring Competitiveness in the travel and tourism industry. Discussion Paper. Nottingham University Business School, Nottingham. University of Nottingham.
• Hassan, S. S. (2000). Determinants of market competitiveness in environmentally sustainable tourism industry. Journal of Tourism Research, 38(3), pp. 239-245. DOI: https://doi.org/10.1177/004728750003800305
  » https://doi.org/10.1177/004728750003800305
• Heath, E. (2003). Towards a Model to Enhance Destination Competitiveness: A Southern African Perspective. Journal of Hospitality and Tourism Management, 10(2), pp. 124-141.
• Kozak, M., & Rimmington, M. (1999). Measuring tourist destination competitiveness: conceptual considerations and empirical findings. Hospitality Management, 18, pp. 273-283. DOI: https://doi.org/10.1016/S0278-4319(99)00034-1
  » https://doi.org/10.1016/S0278-4319(99)00034-1
• Levin, J., & Fox, J. A (2004). Estatística para ciências humanas. São Paulo. Prentice Hall.
• Medina, I., Ortiz, P. J. C., Álamos-Concha, P., & Rihoux, B. (2017). Análisis Cualitativo Comparado (QCA). Madrid. Centro de Investigaciones Sociológicas.
• Brazilian Ministry of Tourism - MTur, SEBRAE, & Fundação Getulio Vargas - FGV. (2013). Competitiveness Study of 65 Destinations Inductor of Regional Tourism Development. Brasília.
• Brazilian Ministry of Tourism - MTur. (2012). Study of the Domestic Tourist Demand 2012. Brasília.
• Brazilian Ministry of Tourism - MTur. (2013). Study of the International Tourist Demand 2013. Brasília.
• Ragin, C. C. (1987). The Comparative Method: Moving Beyond Qualitative and Quantitative Strategies. Berkeley, Los Angeles and London: University of California Press.
• Ragin, C. C., Shulman, D.,Weinberg, A., & Gran, B. (2003). Complexity, generality and qualitative comparative analysis. Field Methods, 15(4), pp. 323-340. DOI: https://doi.org/10.1177/1525822X03257689
  » https://doi.org/10.1177/1525822X03257689
• Rihoux, B., & Meur, G. (2009). Crisp-set qualitative comparative analysis (csQca). In: Rihoux, B., Ragin, C. C. (2009). Configurational comparative methods: ... Thousand Oaks CA: Sage Publications.
• Ritchie, J. R. B., & Crouch, G.I. (2010). A Model of Destination Competitiveness/ Sustainability: Brazilian perspectives. Revista de Administração Pública, 44(5), pp. 1049-66. DOI: https://doi.org/10.1590/S0034-76122010000500003
  » https://doi.org/10.1590/S0034-76122010000500003
• Rivero, M. S., & Caldera, M.A.F. (2004). The competitiveness of tourist destinations: a quantitative analysis using logistic models. Application to the Extremadura municipalities. I Jornadas de Economía del Turismo. Palma de Mallorca, May 28-29.
• Rodrigues, L., & Carrasqueira, H. (2011). A Comparative Analysis of Sun and Sea Tourist Destinations Competitiveness. The Case of the Algarve vs. Southern Spain. Estudios y Perspectivas en Turismo, 20, pp. 855-875.
• Sette, I. R., Santos, G. E. O., & Uvinha, R. R. (2017). Modelos de Competitividade de Destinos Turísticos: evolução e críticas. Revista Acadêmica Observatório de Inovação do Turismo, 11(1), pp. 92 - 115. DOI: https://doi.org/10.14210/rtva.v19n2.p292-318
  » https://doi.org/10.14210/rtva.v19n2.p292-318
• Sette, I. R., & Tomazzoni, E. L. (2017). Os desafios, as limitações e as perspectivas do modelo do Índice de Competitividade Turística no contexto da Política Nacional de Turismo brasileira. Turismo, Visão e Ação, 19(2), pp. 292-318. DOI: https://doi.org/10.14210/rtva.v19n2.p292-318
  » https://doi.org/10.14210/rtva.v19n2.p292-318
• Taberner, J. G. (2007). Proposal of two indices for the Measurement of the Competitiveness of the Sun and Sand Destinations of the Mediterranean. Revista de Análisis Turístico, 4, pp. 50-67.
• Wagemann, C. (2012). ¿Qué hay de nuevo en el Método Comparado?: QCA y el análisis de los conjuntos difusos. Revista Mexicana de Análisis Político y Administración Pública, 1(1), pp. 51-75.
• World Economic Forum (2015). The Travel and Tourism Competitiveness Report 2015. Switzerland.

• *
  Authors acknowledge the financial and institutional support from Brazilian National Council for Scientific and Technological Development - CNPq (Projects 307976/2013-0 and 471589/2014-4) and the institutional support from the Brazilian Ministry of Tourism.

• Peer-reviewed article.

Publication Dates

• Publication in this collection
  01 July 2019
• Date of issue
  May-Aug 2019

History

• Received
  02 Nov 2018
• Accepted
  03 Jan 2019