TOURISM: SCIENTIFIC PAPERS

Competitiveness of tourist destinations: demand and performance factors

Competitividade de Destinos Turísticos: fatores de demanda e desempenho

Carlyle Tadeu Falcão de Oliveira*, Deborah Moraes Zouain**, Luiz Alexandre Valadão Souza***, André Luís Faria Duarte****

* Universidade do Estado do Rio de Janeiro - UERJ, Brazil, carlyle.falcao@gmail.com

** Universidade do Grande Rio - UNIGRANRIO, Brazil, deborahzouain@gmail.com

*** Universidade do Grande Rio - UNIGRANRIO, Brazil, luiz.alexandre.valadao@gmail.com

**** Universidade do Grande Rio - UNIGRANRIO, Brazil, alduarte@cnen.gov.br

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ABSTRACT

The present article aims to answer whether tourists and experts have different views on factors that impact tourism at a destination. To that end, we used a qualitative approach and adopted the Critical Incident Technique, which allows respondents to express particular needs and expectations. Data were collected through open-ended questions, the answers were recorded, and notes were taken about the interviewees and relevant parts of their narrative. Data were submitted for content analysis and examined in light of the Brazilian competitiveness model. We considered 77 interviews and classified 209 critical incidents. Results showed that half of the critical incidents did not fit into the analysis categories proposed in the Brazilian competitiveness model, with nine “new categories” emerging in the process. Therefore, there is a difference of perspective between the visitor and the expert concerning what is more important about tourism at a destination.

Keywords: Brazil, tourism, competitiveness, critical incident technique, destination performance.

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RESUMO

O presente artigo busca responder se existe a diferença de visão entre especialistas e turistas sobre factores que impactam o turismo em um destino. Este trabalho baseou-se em uma abordagem qualitativa e adoptou o Método de Incidentes Críticos, que permite ao respondente expressar necessidades e expectativas específicas. A recolha de dados foi realizada por meio de perguntas abertas, tendo o seu conteúdo sido gravado, e realizados apontamentos sobre os entrevistados, assim como dos trechos relevantes da narrativa. Os dados foram submetidos à Análise de Conteúdo e à luz do modelo brasileiro de competitividade. Foram consideradas 77 entrevistas e classificados 209 incidentes críticos. Os resultados mostraram que metade dos incidentes críticos não se encaixavam nas categorias de análise propostas no modelo brasileiro de competitividade, surgindo nove “novas categorias”. Há, portanto, uma diferença entre a perspectiva do visitante e a do especialista em relação ao que, de fato, é mais importante sobre turismo no destino.

Palavras-chave: Brasil, turismo, competitividade, método de incidente crítico, desempenho do destino.

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1. Introduction

In Brazil, tourism is seen as a significant tool for socioeconomic development and as an industry capable of promoting economic growth and improving the region’s social, cultural and environmental areas (Ministério do Turismo, 2013). From this perspective, evaluating the factors that promote or hinder tourism is strategically important for the country that seeks to provide high-quality products while creating an innovative concept of competitiveness.

The trend of measuring a country’s competitiveness with the objective of classifying it has become routine for both countries and entities within the economic and tourism sectors, as can be seen in works by the World Economic Forum (WEF) at a global level, and by the Ministry of Tourism in the period from 2008 to 2015 in Brazil.

Although the phenomenon of competitiveness has been the subject of much discussion and academic output in the field of tourism, little is said about the competitiveness of tourist destinations from the point of view of demand, i.e., destinations’ competitiveness from the perspective of the visitors. Therefore, this present study aims to demonstrate how it is possible to include the perspective of demand, translated by the tourist experience, thus providing a fine-tuning of the instruments used for measuring competitiveness in tourism. To that end, we will demonstrate that the different models of tourism competitiveness known in literature are structured essentially in terms of supply factors and that the tourism competitiveness model used in Brazil from 2008 to 2015 is not that compatible with the perspective of those who visit the destinations - tourists.

The present article aims to answer whether there is a difference of vision between experts and tourists on factors that impact tourism at a destination. It builds on the assumption that the models of destination competitiveness measurement are essentially focused on supply factors and were designed by scholars and industry experts, thus providing a vision that may be distant from what is perceived by the consumer-tourist. Therefore, the goal of this study is to determine whether there is a difference of vision between experts and tourists on factors that impact tourism at a destination.

2. Competitiveness of Tourist Destinations

The literature on tourism has a number of international experiences and studies on competitiveness in the tourism industry. Of these, four models stand out as most representative due to the number of citations in the literature: the Crouch and Ritchie model (1995, 1999); the Dwyer and Kim model (2003); the Gooroochurn and Sugiyarto model (2005); and the WEF model (Blanke, 2007).

Crouch and Ritchie (1999) developed a conceptual model of destination competitiveness based on a review of studies on the determinant factors of demand for international tourism, public policy planning and the image of tourist destinations. The model takes into account a total of 36 attributes (influential variables) of tourism competitiveness divided into five groups denominated as follows: core resources and attractors; supporting factors and resources; destination management; destination policy, planning and development; qualifying and amplifying determinants (which determine destination competitive potential).

The model of Dwyer and Kim (2003) is made up of four dimensions that define the competitiveness of a destination: resources, tourism destination management, situational conditions and demand conditions. The resources dimension consists of a destination’s characteristics that make it attractive to a potential visitor. The situational conditions dimension is comprised of all the factors related to the impact of the external environment, i.e., how politics, economy and technology affect destination competitiveness. The destination management dimension is divided into tourism industry factors and government factors. The demand conditions dimension includes three basic elements: identification, perception and preferences. Dwyer and Kim (2003) underline the fact that tourism destination competitiveness indicators are just the result of discussions with groups of experts. Since the destination is ultimately chosen by the consumer - i.e., the tourist - it would be appropriate to check how valid the model can be for this group.

Gooroochurn and Sugiyarto (2005) designed a model to assess tourism destination competitiveness featuring units of analysis: price, economic openness, technology, infrastructure, human tourism, social development, environment and human resources.

The WEF published a significant study on tourism competitiveness in 2007, based on secondary data from various international agencies, as well as a survey with leaders and executives attending the forum (Blanke, 2007). The study built tourism competitiveness rankings in which 130 countries were classified according to their level of competitiveness. This study has been repeated annually by the WEF.

The competitiveness index developed by the WEF was based on a model comprising 13 key elements: policy rules and regulations; environmental regulation; safety and security; health and hygiene; prioritization of travel & tourism; air transport infrastructure; ground transport infrastructure; tourism infrastructure; ICT infrastructure; price competitiveness in the T&T industry; human resources; national tourism perception; and natural and cultural resources (Blanke, 2007).

In recent years, the literature on destination competitiveness has been enriched by other contributions.

Wu, Lan and Lee (2012) criticized the WEF Competitiveness Index by suggesting that the model gave the various competitiveness subindexes and pillars the same importance, thus limiting the quality of the information provided to policymakers and hindering better decision-making processes. The authors explored the causal relationships between the subindexes and pillars that affected WEF competitiveness index rankings. They proposed for the variables used by the WEF an objective weighting system based on a set of quantitative methods involving: Data Envelopment Analysis (a multivariate technique for monitoring the productivity of decision units); Bayesian Network (in order to classify cause-effect hypotheses); and Least Squares Model for hypothesis testing using structural equation modeling.

Dwyer, Cvelbar, Edwards and Mihalic (2012) discussed tools to measure destination performance through ImportancePerformance Analysis (IPA). The IPA model was used to assess Slovenia’s competitiveness according to two dimensions: important resources and their respective performance. Their results provided information on the best performing resources as perceived by Slovenia, and those in which the country has the greatest importance-performance gaps. These results also provide empirical support for scholars regarding both the tourism industry and improvements in destination resources. The authors suggest that resource competitiveness importance can vary from place to place depending on the product mix and target audience. The authors used the following factors to measure the destination’s competitiveness: sustainable development; risk management; marketing; education for tourism and hospitality; and climate change.

Risteski, Kocevski and Arnaudov (2012) developed three concepts for achieving destination competitiveness: development of sustainable destinations; destination management planning; and implementation of integrated quality management. The authors considered that the quality and integrated management of a tourism destination are linked to spatial planning and development issues. Thus, a destination’s spatial planning must incorporate sustainable tourism into a holistic, integrated approach.

Croes and Kubickova (2013) designed a tourism competitive index derived from satisfaction, productivity and quality of life. The authors claimed that a meaningful measurement of tourism competitiveness is performance (an ex post concept) rather than efficiency (the ex post concept proposed by the WEF competitiveness index). The authors measured tourism competitiveness in six Central American countries based on these three concepts and on the assumption that successful destinations seem to be strongly correlated with the quality of life of their residents. The study indicates that in countries where tourism is evolving, it is directly related to public policies. They also identified two important attributes of these countries that are conducive to tourism development: high per capita income and value-added (this implies a specialisation in tourism). These last two attributes, according to Croes and Kubckova, drive quality of life in destinations.

Botti and Peypoch (2013) developed a model that combines Multi-Criterion Decision Analysis (MCDA) and Elimination and Choice Expressing Reality (ELECTRE I). They applied this construct to four Hawaiian islands in order to analyze their relative tourism destination competitiveness. The competitiveness factors in this model were the same as the ones mentioned in the literature by Crouch and Ritchie (1999). They showed that the foundations of tourism destination competitiveness are: destination management; destination policy, planning and development; qualifying and amplifying determinants (location, costs, security, image, interdependence and load capacity).

Martínez, Galván and Lafuente (2014) introduced public policies and tourism marketing as determinants of destination competitiveness. They presented the results of a field study conducted in two tourist destinations recognized as World Heritage Sites by UNESCO. Their research included 23 items related to the following factors: public policies, foreign direct investments (FDI), tourism marketing, cultural resources, human resources, quality and price of services. According to their results, in the cities studied, tourism competitiveness stems from the relationships between the following factors: marketing, FDI, public policies, human resources and cultural resources. They concluded that to meet the needs of hosts and visitors, both the government and the private sector should jointly promote the required guidelines, strategies and actions.

Research on the competitiveness of Brazilian tourism destinations has been one of the main goals of Brazil’s National Tourism Plans since 2007. In the period from 2007 to 2015, the Ministry of Tourism used a particular research methodology to identify tourism destinations that could be major drivers of tourism development in their respective regions (Ministério do Turismo, 2013).

This methodology was developed by researchers at the Getulio Vargas Foundation, whose model has been adopted by the Brazilian Ministry of Tourism to measure the competitiveness of destinations that drive regional tourism development (Ministério do Turismo, 2013).

This model has five pillars that subdivide into 13 dimensions (Figure 1), which in turn branch out into 62 variables with almost 600 indicators. Data are collected in each destination through direct observations and interviews with publicand private-sector managers directly or indirectly involved with tourism. Secondary data complement the collection so that competitiveness can be calculated through a weighted average of these variables and dimensions.

 

 

As can be seen in the models presented above, including the factors they use to measure competitiveness, the focus is on destinations’ structural characteristics, that is, on tourism supply factors. Competitiveness analyzes are carried out exante, i.e., by efficiency. Thus, the competitiveness of a destination is analyzed before tourists even arrive. One explanation for this can be found in a study by Oliveira (2013, p.84) in which he says that the reason for the prominence of supply over demand factors resides in the goals of these studies: “diagnosing installed capacity; generating strategic information for decision making; monitoring and measuring structural competitiveness”. Ideally, competitiveness would also be analyzed ex post, i.e., according to performance, by analyzing whether the tourist had a satisfactory, enjoyable experience.

Another key point concerns the origin of data that feed all models presented here. According to Oliveira (2013, p. 85) “the origin of data that feed the models’ indicators is mostly secondary sources published by international agencies and polls with experts in the field”.

The exception is the model of the Brazilian Ministry of Tourism, which uses field research through interviews and observations complemented by secondary data. However, the subjects interviewed are experts directly or indirectly related to tourism. None of the models designed to measure the competitiveness of destinations operates with tourists’ opinions.

Therefore, a tool that incorporates the perspective of tourism demand into competitiveness models would complement research on the subject. From an epistemological point of view, this would involve bringing a more interpretivist vision to the phenomenon of destination competitiveness and comparing it to the positivist bias used in the models presented here, that are based on the variables of tourist attractions and the supposed cause and effect.

Tourists’ opinion concerning their satisfaction with the so-called tourism product - the set of attractions, services and infrastructure that tourists are offered - takes into account a number of attributes of the destination. In this respect, many studies explore the performance of a particular destination by analyzing tourists’ statements (tourism demand) on how satisfied they feel about the various aspects of the destination (Alegre & Garau, 2010, Alegre & Cladera, 2006, Baker & Crompton, 2000, Kozak, 2002, Kozak & Rimmington, 1999, Yoon & Uysal, 2005).

Tourist satisfaction is viewed as an indicator of competitiveness (Enright & Newton, 2004). Several studies have used satisfaction surveys to gather information on tourists’ opinions in order to assess destination performance (Alegre & Garau, 2010). In these studies, tourist satisfaction is generally measured post facto, either globally or by assessing the attributes of the place, and it can be translated as tourism demand determining destination performance.

In relation to tourism services, it is worth highlighting the study of Cadotte and Turgeon (1988), who were the first to examine the dissatisfaction and satisfaction variables in the hospitality industry. Yu and Goulden (2006) focused their research on understanding tourists’ levels of satisfaction with their destination experience as they thought this was essential for improving products and services. Thus, they could promote a destination in target markets in order to increase the flow of visitors and win new client-tourists.

Maunier and Camelis (2013) consider that a bi-factor approach (i.e., satisfaction and dissatisfaction) is as relevant for destinations as it is for companies. The overall satisfaction of individuals towards a tourism experience can be optimized by improving elements that create satisfaction, while avoiding sources of dissatisfaction. Tourism, according to Costa (2014) grew from classical logic, formed around products, into a perspective in which the touristic experience is valued.

Therefore, the present work considers the experience of tourism in a holistic way, i.e., as the tourist’s interpretation of a succession of experiences and services of different natures (private and public) which are linked together by the touristconsumer during his or her stay in the destination.

3. Methodology

The critical incident technique (CIT) proposes a reliable and exhaustive measure of tourist satisfaction, integrating elements directly linked both to the destination and to the activities and services delivered to the visitor (Maunier & Camelis, 2013).

The CIT was proposed by Flanagan (1954) and is essentially a procedure for combining certain important facts about the behavior of defined situations, and is more a flexible group of principles that must be modified and adapted to understand the specific situation rather than a rigid body of rules that rule this collection of facts. (Flanagan 1954). It’s useful for exploring significant experiences, with the objective of better understanding behavior (Batle & Robledo, 2018). The use of this technique permits that the decision about which situations will present a crisis can be left to the participant, instead of being imposed by the researcher (Andirin, Moital & Cardoso, 2017).

This technique has a more interpretivist perspective that provides the competitiveness models with a counterpoint to the techniques of a more positivist slant. Despite counting on the subjective vision of visitors to destinations to create a body of perceptions about experiences at a destination, the CIT is a scientifically valid instrument for measuring tourist services.

Alegre and Garau (2010) and Maunier and Camelis (2013) used CIT to investigate the main drivers of tourist satisfaction and dissatisfaction in destinations visited. According to Alegre and Garau (2010), who focused on explaining the need to use CIT to survey tourists, traditional surveys were not efficient enough to identify in a destination the critical points that brought satisfaction or dissatisfaction to tourists. In turn, the study of Maunier and Camelis (2013) used CIT to analyze the tourist experience in a holistic way and propose a typology of elements that contributed to tourist satisfaction/dissatisfaction in the destination. The authors suggested new attributes to be observed by public authorities and business people in the tourism industry that could positively or negatively impact the tourism experience in the destination.

The main goal of the present study is to bring into studies of tourism destination competitiveness the dimension of demand. To that end, we used CIT both to capture the demand perspective and to be a new instrument to be incorporated into studies of tourism competitiveness, since it has already been used by authors (Callan, 1998; Crotts & Pan, 2007; Petrick, Tonner, & Quinn, 2006; Pritchard & Havitz, 2006) in research on tourism and hospitality, including assessments of satisfaction in tourism destinations (Alegre & Garau, 2010, Maunier & Camelis, 2013).

The interviews took place from July to September 2013, with people who had traveled within Brazil in the two previous years. The decision to consider up to two years prior to the interviews is in line with Maunier and Carmelis (2013) and Pritchard and Havitz (2006), who consider this an acceptable limit for interviewees to recall in detail some critical incident. As for interviewing only domestic tourists, this is related to our decision to limit destinations to the Brazilian context because its socioeconomic characteristics are more familiar to us and because of the use of the Brazilian model, which was designed for national destinations.

We used the snowball method, which is a non-probabilistic sampling technique to access interviewees. We interviewed students at a higher education institution in the city of Rio de Janeiro, as well as their relatives; students at a college in the city of São Gonçalo, in the state of Rio de Janeiro, as well as their relatives; and people of various occupations in the city of Cuiabá, in the state of Mato Grosso.

A total of 80 people who had traveled in the two previous years were invited to recall their latest travel experience within Brazil and to report specific events that caused them pleasant or unpleasant feelings during their stay, regardless of the destination and reason of their trip. This two-year period was critical to validate the critical incident as it allows recalling the details of the travel experience. Respondents were not directly asked to identify the underlying causes of satisfaction or dissatisfaction, but rather describe a specific example of pleasant and/or unpleasant experience. It is the researcher’s responsibility, not the interviewee’s, to abstract and infer (Bitner, Booms, & Tetreault, 1990). The interviews were recorded and then transcribed with Atlas.ti software, which was also used to categorize the variables and sub-variables in this study. The interviews lasted between 5 and 12 minutes. This amount of time was enough to capture the critical incidents of the narratives.

Not all narratives were considered as critical incidents. We used the criteria of Bitner et al. (1990) for considering an incident critical: (i) being directly related to a tourism event, from departure to return (this excludes, e.g., booking and post-trip services); (ii) being very satisfying or dissatisfying from the customer’s point of view; (iii) being a discrete episode; and (iv) having sufficient detail to allow interpretation by the researcher. Thus, three of the 80 interviews collected were discarded, one because it was not directly related to a tourism event as described in item (i); and two because they were not classified as very unsatisfying events, thus failing to meet item (ii).

We used content analysis (CA) to analyze the data, since according to Maunier and Camelis (2013), CIT is essentially a classification technique that employs CA and has stories or incidents as data.

The dimensions (Figure 1) and variables established by the model of the Ministry of Tourism (Ministério do Turismo, 2013), provided a framework for the categorization process. Consistency of results was obtained by following the recommendations of Butterfield, Borgen, Amundson and Maglio (2005) for determining the credibility and reliability of a study conducted through CIT.

Due to the limitations of this method, it is recognized that the motivation for the trip that led the visitor to search for a destination wasn’t touched on in this study. This factor could be a differential in the tourist’s perception of satisfaction or dissatisfaction. Another limiting factor could be that the tourist’s experience and the tourist’s contact with services and visited locations happen simultaneously. The time gap between the experience and the narrative of the interviewees could distort the narrative perspective.

While there may be other demand factors that are significant for measuring the impacts of tourism, like the economic dimension that observes tourist consumption at destinations, this is outside the scope of this research. The focus of this study is on the tourist experience at a location and how this can be analyzed from the point of view of competitiveness.

4. Analysis of results

We identified a total of 209 critical incidents (CIs) in the 77 valid interviews. Of those, 88 were considered positive incidents or satisfying experiences, and 121 negative or unsatisfying experiences. The elements that contributed to tourist satisfaction or dissatisfaction were classified a priority according to the 13 dimensions which are subdivided into the 62 variables of the Brazilian competitiveness model (Ministério do Turismo, 2015). A total of 9 new categories emerged which were later submitted to a panel of three experts to confirm their classification. It is worth noting that a narrative may have more than one critical incident relating to satisfaction or dissatisfaction.

Of the total of 209 critical incidents (CIs) recorded, 105, i.e., half were identified and categorized by the dimensions and variables of the Brazilian model. The other half, consisting of 104 CIs, were not captured by the competitiveness parameters proposed in this model. Therefore, we designated them as new categories of analysis, which we describe in this section.

4.1 Critical Incidents (CIs) captured by the model of the Ministry of Tourism (MTur)

The 105 critical incidents (CIs) captured by the MTur model fall under the following categories (in absolute numbers): tourist attractions - 45 CIs; access - 25 CIs; general infrastructure - 21 CIs; tourism services and equipment 12 CIs; local economy - 1 CI; environmental aspects - 1 CI. There were no reported cases that could be classified under the following categories (dimensions): Marketing; Public Policy; Regional Cooperation; Monitoring; Business Capacity; Social Aspects; Cultural Aspects.

4.2 Critical Incidents (CIs) not captured by the model of the Ministry of Tourism (MTur) - new categories

It is worth noting that these “new categories” are not innovative within the literature if analyzed from the supply perspective, but when studied in the light of demand, they have a differentiated connotation that is associated to destination performance.

• Hospitality of residents towards visitors - 21 CIs.

• (In)security perceived by tourists - 22 CIs.

• Discomfort caused by poverty and prostitution - 10 CIs.

• (Dis)satisfaction with services (tourism and others) - satisfaction or dissatisfaction with the quality of services - 32 CIs.

• Other categories: harassment by street vendors (of products or services) - 6 CIs; food and tourism service prices

• 7 CIs; lack of shopping options - 4 CIs; air pollution - 1 CI; excess of visitors at the attraction - 1 CI.

5. Discussion

The category with greatest impact for interviewees was tourist attractions, with 45 recorded critical incidents being mentioned by 58% of respondents. According to the literature, tourist attractions (whether natural, cultural or artificial) are responsible for the movement of people from their place of origin to their destination. The attractions are the inputs of the tourism destination that combine with services and infrastructure to form the system’s output, i.e., the tourism product (Beni, 2001; Cooper, Fletcher, Fyall, Gilbert, & Wanhill, 2001; Oliveira, 2001).

Tourist attractions are resources that belong to the destination and are legally delimited by the city or municipality. This factor is usually measured in the literature by documentary and bibliographic research, except for the Brazilian model, which uses primary data (interviews and observation) in addition to secondary data. Thus, this model is more suited for tourism planners for two reasons. First, it is the only model that uses the city/municipality as the unit of analysis, since that is where attractions are. Second, directly observing attractions brings the researcher's perspective closer to that of the visitor, so as to cause in the former an experience similar to what is perceived by the latter. The tourist experience caused by observing the attraction and its aggregate elements (maintenance, facilities, access) is the one that most closely approximates the destination’s performance, since attractions are the main motivation for visiting, thereby requiring much attention from tourism scholars and managers.

In the access category, there were 25 CIs, accounting for 32% of critical incidents. The analysis of competitiveness in terms of access covers the existence and conditions of airports, roads, highways, airlines, bus lines, city traffic, among other factors. Also in this category is “destination transport system”, the item that interviewees mentioned most. This is in line with the conclusions of Thompson and Schofield (2007) that public transport availability and performance were an important attribute to overall tourist satisfaction. Visitors are not restricted to lodging and attraction environments. They circulate around the destination, whether for shopping, food or experiencing the destination. Transport system use is also determinant to the degree of user satisfaction. The performance of access-related factors is not properly assessed by competitiveness surveys, as these evaluate this category essentially in terms of installed capacity, i.e., on the supply side.

Another category with a significant weight for the destination was “general infrastructure” (27%), particularly urban infrastructure. This competitiveness factor concerns the local urban landscape. Street paving, lighting, squares, gardens, road signs, safety and cleanliness can positively or negatively affect visitors’ perception. Observing urban facilities provided the main source of data for indicators in this category. As with “tourist attractions”, the observer's perception of the urban landscape, as well as his or her contact with it, can determine the level of tourism experience. An exception to this category is the urban security system, which was assessed for its installed capacity, while using secondary data source, as well as interviews with public authorities. However, in the tourist’s eye, public security can only be checked through the tourist’s own experience, during the time he or she stays in the destination.

The “tourism services and resources” category accounted for only 16% of CIs. The fact that few interviewees referred to tourism services is an example of how supply/efficiency and demand/performance analyses are complementary. This dimension considers secondary and primary data in order to analyze the existence of tourist signage, information points and service types; however, it does not evaluate the quality and availability of services, which are only assessed by the consumer. Therefore, only interview responses mentioning incoming operator services and resources, lodging facilities, restaurants and tourist information were recorded in this category. Satisfaction or dissatisfaction with these services was recorded in a new category (i.e., service quality), as discussed below.

Thus, let us now discuss the “new categories” of competitiveness revealed by data from the present work, relating them to the competitiveness models studied.

Satisfaction or dissatisfaction with services was mentioned by 42% of the interviewees, which shows the importance of this factor for destination competitiveness. However, no empirically-tested competitiveness model analyzes the quality of services experienced in the destination. It is worth noting that Dwyer and Kim (2003) suggest incorporating subjective factors of demand into models designed to measure competitiveness in tourism. These demand factors also translate the destination’s service performance as they express how tourists experience services therein. Many services are directly linked to tourists’ experience of local attractions such as tour guides, tours, signage, transportation, food, lodging and entertainment. It is understandable for models to try to determine the capacity of these services through their indicators, but only experiencing will confront what is offered with what consumers expect to have. Out of this confrontation comes tourists’ satisfaction or dissatisfaction.

Thus, the variables of competitiveness studies take into account factors that can assess a destination’s ability to offer good services. That is the case with “capacity to train and work with local people” and “tourism qualification structure” in the Brazilian model, which are not mentioned by the demand as important; however, according to researchers/experts, those are ways of analyzing ex-ante the destination’s ability to provide quality services. It is noteworthy that service supply is not restricted to tourism. Business and events visitors may demand other services than tourist ones.

In this respect, other competitiveness factors can be found in the models dedicated to events and business tourism, such as the following variables: “aspects of the local economy”, “communications infrastructure” and “business infrastructure and facilities”. These factors did not appear in the interviews, but their importance is understandable due to their impact on the destination’s service quality. Again, experts are concerned with covering several aspects that can contribute to local competitiveness by analyzing the structures installed in the destination.

The feeling of insecurity was reported by 29% of respondents as being a critical event in their travel experience. This is another typical case of performance by (public) services responsible for providing security for visitors in the destination. The Brazilian model checks the public security structures in place, yet without determining whether they are sufficient to control all variables affecting the feeling of (in)security perceived by visitors. The interviews showed that insecurity stemmed from street robbery, begging, drug users/street dwellers and harassment by street vendors.

Street robbery is the greatest symbol of the violence committed against tourists, but the deep social inequalities which mark the Brazilian reality stress the social exclusion underlying the situations of begging, street dwellers using drugs and harassment by street vendors. Without going further into the country’s social imbalances, some factors of tourist insecurity stem from destination sustainability issues, especially those related to the “social aspects” dimension. However, there are no indicators designed to capture these factors in the competitiveness models studied.

The Brazilian model tries to identify the problem of social imbalances, but it only checks for the existence of public policies whose factors involve “citizenship”, “access to education”, “democratization of attractions”, “jobs created by tourism” and “prevention of child sexual exploitation”. These factors reflect an ex-ante analysis, like the competitiveness factors related to public security described earlier. Thus, social exclusion is at the origin of some causes of dissatisfaction we found which affect destination competitiveness and are only captured by ex-post analyzes: insecurity, harassment by street vendors, discomfort caused by prostitution (including child/juvenile prostitution) and poverty.

This social exclusion is not limited to urban areas. Rural areas, too, can suffer from social imbalance, as can be seen in movements like the “landless workers movement” (MST) which mark rural and natural landscapes where major environmental preservation areas (APAs) are located.

In sum, the social sustainability dimension can heavily affect Brazilian tourism competitiveness.

The hospitality mentioned by 27% of interviewees as a critical incident refers to the act of welcoming visitors rather than the business of providing lodging in exchange for payment. The best way to show hospitality is to treat visitors in a way that makes them feel welcome. This can take place in the streets through good-will gestures by residents as they give directions, advice or listen to those who do not know the area. As regards to tourism professionals, a hospitable attitude should be a conscious duty. As for the recipient population, it is a matter of awareness raising. Though hospitality is a key factor for destination competitiveness, there are no indicators for capturing this aspect in the Brazilian model.

The WEF and the Crouch and Ritchie (1995, 1999) models have hospitality indicators, but the data sources are questionnaires answered by tourism professionals and scholars analyzing countries. This means there may be considerable distortions between the hospitality experienced by those who visit a city and the opinion of experts about the hospitality of residents of an entire country, as with the competitiveness models described here.

The contact between visitor and visited is inevitable in a destination. It takes place in passenger terminals, public transportation, restaurants, shopping areas, attractions and streets. Whether in services or in casual contact, there will be some kind of interaction between these two tourism actors. Therefore, the tourism experience is important for checking the competitiveness of the destination in terms of hospitality so as to monitor the effectiveness of public policies to raise the awareness of the native population for tourism.

Other critical incidents have been reported less frequently than the ones mentioned above, but still deserve attention from managers due to three elements: demand segmentation, tourism destination vocation, and sustainability.

Another gap in the Brazilian model compared to the others is the absence of the price variable. Depending on the tourist segment that is being targeted, price is not only a competitive factor but an essential one. Not all destinations can offer tourism products that reach the highest social strata, whose high consumption standards are less sensitive to top prices. In a competitive environment, tourists of medium and low socioeconomic classes will seek better price conditions in the market, which will result in choosing a destination that can offer them more economical “travel packages”. The price variable is present in all other destination competitiveness models we examined in this study, and it should be incorporated into the Brazilian model.

Although there is not officially a shopping tourism segment, flows of tourists are known to also travel with that purpose. There are "travel packages" marketed by travel agencies with this purpose. The “shopping” factor may not be the trip’s main motivation, but it can heavily influence certain groups of tourists, serving as a complementary activity to visitors in their free time.

Availability of shopping places, product diversity and price are factors deserving study for purposes of destination competitiveness according to Dwyer and Kim (2003), whose model was the only one to include this feature. The “shopping” factor can be easily incorporated into the competitiveness models as it can be analyzed by the installed capacity of these facilities alone since the reason for the dissatisfaction or satisfaction found in this study is not directly related to the product, but to its availability.

Two categories which emerged from the interviews and were not captured by the Brazilian model (or any other model) relate to environmental sustainability: air pollution and overcrowding in tourist venues.

The Brazilian model is the most comprehensive on sustainability criteria as it evaluates the four main dimensions of sustainability (i.e., economic, social, environmental and cultural). Still, it cannot translate in competitiveness terms what one perceives while in direct contact with the surrounding environment. That is the case with the “monitoring” category, which aims to assess whether the destination has the means to measure the impacts of tourism; and “environmental aspects”, whose indicators are, among others, the existence of environmental legislation and of potentially polluting activities.

These factors are analyzed before the tourism product is consumed so that its effectiveness is only perceived at the place of the experience. Put another way, it is the performance assessment of the “monitoring” and “environmental aspects” factors that will confirm whether the destination is environmentally sustainable.

Likewise, other dimensions of the competitiveness model with their respective variables and indicators will try to translate competitiveness in a potential way, i.e., through an ex-ante analysis. The “marketing” dimension will deal with the destination’s image and strategy to attract and retain tourists. The “public policy” dimension will map tourism organizations and governance, destination strategy and government and public-private cooperation networks. Finally, there will be a destination potential competitiveness survey (efficiency assessment) which will only be confirmed through an ex-post analysis (performance assessment).

This is in line with Lastres and Cassiolato (1995), who consider the efficiency approach a restrictive one as it treats competitiveness in a static way, allowing the analysis of indicators at a particular point in time. Therefore, the demand factor can be the dynamic element that will adjust the tourism product according to visitors’ expectations. Thus, the critical incident technique (CIT) can be a fundamental tool for capturing feedback from demand (the tourist experience) regarding the performance of the tourism product, while supplying destination managers with strategic information for the system’s stability.

Thus, there must be a suitable system of permanent planning to organize activities and promote local development policy, to which the participation of the public sector is indispensable.

According to Paiva and Manfredini (2010), there is a major gap in the state apparatus for defining public policy on competitiveness. The issue of destination management is a complex one due to the multiple actors who must work as a network to achieve competitiveness in the tourism market, but whose individual goals are possibly conflicting. In this respect, Paiva and Manfredini (2010) say that tourism destination competitiveness will necessarily involve a process of improving management policies and evaluation tools for decision making.

Finally, competitiveness researchers and tourists are not in complete agreement on which should be the most important factors of competitiveness in tourism. In the case studied, half of the 209 CIs escaped detection by the Brazilian model, and nine new categories might well be added to the construct. In fact, the Brazilian model delimited its scope by adopting competitiveness indicators based on efficiency concepts (ex ante). Therefore, it is hardly surprising that “new categories” should emerge from field research. These results are in line with the studies of Eysteinsson and Gudlaugsson (2012, p. 112), who conducted a survey in Iceland precisely to determine whether experts and tourists attributed the same values to 10 factors selected from the literature on destination competitiveness. They found that the two groups did not necessarily have the same opinion. Hence the importance of knowing the opinion of the tourist in competitiveness studies.

Therefore, research on demand using the Critical Incident Technique (CIT) provides competitiveness studies with the possibility to test selected variables for their performance in order to measure the destination’s global competitiveness.

6. Conclusion

This article argued that models for measuring tourism destination competitiveness are essentially based on offer and were designed by scholars and tourism professionals, thereby lacking an instrument to capture the perspective of tourism demand. Thus, the main goal of our study was to describe how incorporating the tourist’s experience at a destination into competitiveness studies through CIT can be used both to adapt the tourism product to its demand and as a performance measurement instrument.

CIT is a viable tool for capturing the tourist’s experience and we tested it with different types of tourists visiting various national destinations. We identified a total of 209 critical incidents (CIs). Of this total, 105 CIs, i.e., half were identified and categorized by the dimensions and variables of the Brazilian model. The other half, consisting of 104 CIs, were not captured by the competitiveness parameters proposed in this model. They were: hospitality of residents towards visitors; (in)security perceived by tourists; discomfort caused by poverty and prostitution; (dis)satisfaction with services (tourism and others); other categories - harassment by street vendors (of products or services), food and tourism service prices, lack of shopping options, air pollution, excess of visitors at the attraction.

From the results of this research, it is possible to draw theoretical contributions to the field of tourism competitiveness, contributions to tourist destination management and monitoring, and subjects for future research.

The following contributions are worth highlighting. First, tourist experience, or demand feedback, can be considered as a performance variable of destination competitiveness. This would allow establishing causal relations between competitive factors and their respective performances. Second, demand feedback can help adjust the tourism product to its public, serving as an important tool for managing product innovation. Third, the analysis of critical incidents can also help improve competitiveness models by establishing new categories and revising existing ones with regard to their weight within the model in order to contribute to global competitiveness; this allows greater accuracy in interpreting reality and diagnosing local tourism conditions. Fourth, this study can be replicated for any Brazilian tourism destination as it is simple to conduct, its operational costs are small, and it can be implemented by central or local governments - with or without private-sector partnerships - who seek a management tool to develop local tourism.

Therefore, we propose a qualitative method for supporting the strength of the quantitative methods of measuring destination competitiveness. Between the interpretivism of the tourist narrative (demand) and the objectivism of the models operated by the variables of tourist attractions, we believe in a more constructivist study in which it would be possible to also count with the tourist perception in relation to his or her experience in a destination.

Our study was restricted to Brazilian tourists visiting national destinations. The perception of foreign tourists should also be studied in future research since people of different cultural backgrounds may react differently to the same stimuli. Tourism products that generate critical incidents (positive or negative ones) to foreign persons may go unnoticed by Brazilians.

We used a convenience sampling method and the number of respondents was small, but our case is in line with Callan (1998) and Andersson and Nilsson (1964), who say a large number of people is not required after the classification of a relatively small number of critical incidents since new categories hardly ever emerge. That was the case with the present work. However, a random sampling process should be used to improve the reliability of the study.

The characteristics of each tourism segment must be examined in competitiveness studies, both in terms of demand and supply. Because supply must be prepared to meet demand, it will be necessary to study competitiveness within specific tourism segments. Therefore, we recommend that tourist motivation be taken into account in future studies.

Our study provided qualitative information on destination competitiveness categories. In order to better measure the weight of each category and its contribution to overall destination competitiveness, a quantitative methodology should also be developed for a better weighting of the factors selected for the model. This would provide a more reliable and robust measurement of competitiveness.

CIT could be incorporated to and tested in electronic media to increase both its range and its access by people who visited a destination and could contribute by leaving an account of their tourism experience, e.g., on the blog of a destination’s website. Capturing accounts through this medium would provide researchers with a database for analysis of critical incidents.

The tourism experience which is observed through critical incidents is produced by a network of organizations in the destination. Studying such networks would bring about new perspectives on stakeholders’ ability to adapt, integrate and reconfigure their resources and skills to be competitive in an ever-changing environment.

 

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Received: 30.11.2018

Revisions required: 21.05.2019

Accepted: 15.07.2019