1. Introduction
From an academic point of view, tourism has aroused a great amount of interest and has been the subject of a great deal of research, which has contributed greatly to a more detailed understanding of the mechanisms that regulate supply and demand in tourism. The marketing literature highlights the importance of the image of tourism destinations as an object of study, as it represents one of the key factors affecting the consumer in all the phases of consumption of the tourism product (Kim et al., 2009; Yilmaz et al., 2009).
The importance of the image as an element that influences tourist behaviour has been treated in the literature, basically, in relation to the “choosing a holiday” phase (Myers, 1992; Pike and Ryan, 2004; Hyde, 2008). In fact, despite the interest that image has aroused in academic research, some authors agree that there is a lack of research regarding the evolution of the image during the different phases of the trip (prior to, during and after the visit) and the influence it has on tourist behaviour (Kim et al., 2009; Yilmaz et al., 2009). As Yilmaz et al. (2009) and Kim et al. (2009) suggested, the results of research into the evolution of the image are of vital importance to the tour operators who, when evaluating the differences between the pre-visit and post-visit image of the destination, and on detecting negative discrepancies, could react with specific marketing strategies. In this context, it would be necessary to determine what factors could be influencing these image differences so that they may be acted upon, becoming the focus of interventions. Tasci and Gartner (2007) considered it relevant to study the antecedents of image formation, assuming that there is a gap between the pre- and post-visit image resulting from all the factors that have influenced the conformation of both constructs.
There is a doctrinal agreement that the image of a destination evolves from a focus on the place and its cognitive components, through the experience of the destination, to a complex post-visit image (MacKay and McVetty, 2002; Lee et al., 2012). As Lee et al. (2012) affirmed, the process of image change gives rise to different results in terms of incongruities: positive when the post-visit image is better than the pre-visit one, or negative when the post-visit image is less favourable. The inconsistency between the pre- and post-visit image influences the tourist experience, satisfaction and post-visit behaviour. For these authors, it is necessary to delve into the intrinsic factors that cause the change between the pre- and post-visit image. The international character of the tourism sector explains the inclusion of culture as a personal factor that can influence the change of image before and after the visit to a tourist destination. In fact, various studies have established the role of culture as an influence on all aspects of consumption and consumer behaviour, and therefore it must be integrated into all elements of consumer behaviour theory (Mooij, 2004). Obviously, knowledge of existing variations resulting from cultural differences can aid in understanding the needs of tourists to meet their expectations (Harris, 2004). According to Hofstede and Hofstede (2005), it is inevitable that people raised in different countries with different cultural norms develop different modes of behaviour and ways of thinking. Therefore, if cultural norms develop differently in different parts of the world, then tourists’ perceptions of the image of a destination will vary according to their cultural background and, more specifically, their capacity to adapt to different and unfamiliar cultures (Balogh et al., 2011).
In this context, cultural sensitivity has been gaining special relevance and becoming a subject of great interest in the tourism sector in recent years, precisely because intercultural interactions are very frequent for tourists, and their ability to adapt to the culture of the destination is influenced by their cultural sensitivity. It is, therefore, an internal factor that influences the behaviour of tourists when choosing a holiday destination. For this reason, this paper aims to analyse the extent to which cultural sensitivity can influence the pre- and post-visit image gap, contribute to the literature by covering this research gap and, at the same time, open up a new line of research into the importance of cultural sensitivity in the tourism sector, for which evidence is currently non-existent.
2. Literature review
Culture, which represents an internal factor of individuals that can influence the image formation of tourist destinations, is defined as the set of beliefs, values, customs, ideas and norms of behaviour accumulated by human beings (Sherry, 1986; Grande Esteban and Alonso Rivas, 2004). Culture has a notable influence on different areas of the life of an individual, as it has an effect on attitudes towards work, on behaviour related to consumption or on leisure activities and, therefore, on the process of choosing a tourist destination (Richardson and Crompton, 1988). In this respect, San Martin and Rodríguez del Bosque (2008) stated that culture is a psychological factor that filters the perception of the individual.
Culture can be influenced by macro-factors, such as the economics, politics, the law, religion, education, technology and industry (Franke and Nadler, 2008; Zhang et al., 2008; Kim and McKercher, 2011). Each macro-area presents some unique characteristics, and when these characteristics are shared by a significant number of citizens of a nation, they become part of national culture (Kim and McKercher, 2011). When the citizens of that nation travel, they will conform to certain behavioural codes, sometimes distinct from their national culture, giving rise to the so-called “tourist culture”. According to Jafari (1987), this change represents a temporary emancipation from everyday life in a non-ordinary world.
In the literature on the influence of culture on the image of a destination, we can find two streams of research. In the first one, the role of culture has been studied as a variable influencing tourist behaviour (Kew, 1979; Reisinger and Turner, 2003; Kim and McKercher, 2011), and in the second as a determining factor in the process of choosing a tourist destination (Correia et al., 2011; Frías et al., 2012). In both cases, it has been observed that culture influences the image of the tourist destination.
In the first research stream, the distinction in the literature between the culture of the individual and the culture of the tourist is relevant. In line with Jafari (1987), during a holiday, the individuals will modify their behaviour to suit the culture of the destination being visited. However, as Carr (2002) and Kim and McKercher (2011) pointed out, during a holiday, individuals will rarely immerse themselves in the culture of the place they are visiting. This conveys to the tourist, despite their ability to adapt their behaviour to the culture of the host country, a perception of the reality of the destination, which is influenced by the cultural elements of their country of origin (Kim and McKercher 2011). In fact, various studies have shown that people coming from different countries or regions, characterised by different cultural values (beliefs, attitudes, customs, meanings and behavioural norms), may have very heterogeneous perceptions about the same tourist destination – that is to say, they will construct different images of the same tourist destination (Richardson and Crompton, 1988; MacKay and Fesenmaier, 1997, 2000; Chen and Kerstetter, 1999; Kozak and Rimmington, 2000). Based on the work of Crotts (2004), San Martin and Rodríguez del Bosque (2008) reached the same conclusion when they analysed tourists’ perceptions of Cantabria based on their different geographical origins, demonstrating that tourists arriving from different countries and, therefore, with different cultural values, have different perceptions of the same tourist destination. However, authors such as Andrade Suárez (2011) and McCartney (2008) showed that cultural distance is not a consequence of geographical distance, as within the same geographical area, culturally distinct individuals can also be found who, therefore, have a different image of the tourist destination. In particular, Andrade Suárez (2011) verified in his work that there is a significant relationship between the geographic-cultural origin of the tourist and the affective dimension of the destination image. The cultural distance of tourists manifests a statistically significant influence with respect to a single cognitive dimension, “social environment and natural and gastronomic attractions”. In this sense, the influence is reduced exclusively to these two aforementioned factors not having any direct effect on the perception of the global image of the destination nor on the rest of the cognitive dimensions.
MacKay and Fesenmaier (1997) analysed the relationship between cultural distance and image to examine the positive or negative effect that culture may have on the formation of the destination image. These authors assert that the smaller the cultural distance, the more familiar the destination is to the individual, and the more favourable will be their impression of the place before and during the holiday.
In the second stream of research, we can find some works that have analysed concretely how culture influences information-seeking behaviour. In this sense, the work of Crotts (2004) showed that the greater the cultural distance perceived by tourists between their own culture and that of the destination they have chosen, the greater would be the perceived risk and, therefore, the need to seek information. This work also details the alternatives that tourists use to reduce this risk: spending more time planning the trip, opting for travel packages, using tour operators as a source of information, opting for group travel, choosing short-duration trips or visiting fewer places of interest. In the same vein, Fuchs and Reichel (2004) pointed out that different cultures are related to different levels of risk perception and that the greater the cultural distance between the place of origin and the destination, the greater is the risk as perceived by the tourist and, therefore, the worse the pre-visit image.
Finally, we must highlight the work of Paramipuspa (2011), in which it was analysed how tourist behaviour was influenced not only by cultural distance but also by sensitivity – defined as the recognition of and respect for different beliefs, values and customs. Therefore, while cultural distance refers to the diversity of customs, religious ideas, politics, etc., sensitivity refers to the ability of culturally distant individuals to adapt to the different cultures of the destination country.
Cultural sensibility corresponds to the emotional component of a broader concept of “cultural intelligence”, the implications of which have been analysed in different works framed in organisational psychology (Earley and Ang, 2003; Earley and Mosakowski, 2004; Ng and Earley, 2006; Templer et al., 2006; Ang et al., 2007). Earley and Ang (2003) defined cultural intelligence as the ability to be effective in situations characterised by cultural differences. According to these authors, individuals with a high level of cultural intelligence are more successful in situations, such as may occur in the workplace, of cultural context change. These authors established the existence of three components of cultural intelligence: cognitive, emotional and behavioural. The cognitive dimension refers to the totality of an individual’s knowledge of different cultures. The emotional dimension represents the propensity of an individual to seek out different cultures, that is, the motivational capacity that pushes one to achieve results in a context of distance from their own cultural moorings. Finally, the behaviour dimension reflects the individual’s ability to act to successfully adapt to the surrounding cultural context. In this same vein, Templer et al. (2006) analysed the relationship between the emotional/motivational factors of cultural intelligence and the possible cultural adaptation of the so-called “global worker”, i.e. professionals who perform all or part of their tasks outside their own country of origin. The results show that global workers with a high motivational level of cultural intelligence are more successful in their work than those with a low level. The work of Triandis (2006) established the factors that can increase cultural intelligence: the level of information that the individual possesses, the ability to eliminate prejudices and the ability to analyse and understand different points of view or perspectives. According to this author, examining the positive and negative attributes of one’s own culture and of others also allows one to increase his/her own cultural intelligence.
In the academic literature, we find different proposals for measuring cultural sensitivity. A great disparity in content and structure is observed among them due to the models and premises from which they initially depart, which has generated some confusion between cultural sensitivity and other related concepts. In respect to this, Chen and Starosta (2000) established five dimensions of cultural sensitivity: commitment in interaction, respect for cultural differences, trust in interaction, enjoyment of interaction and attention to interaction. It is a widely accepted model in the literature, whose five dimensions have been corroborated in the work of Fritz et al. (2002).
Based on the research into cultural intelligence in the field of organisational psychology, Paramipuspa (2011) found that in the tourism sector, individuals with a high level of cultural sensitivity – that is, those who adapt quickly to the culture of the destination – signal a more positive image of the place than those with a low level of cultural sensitivity. In fact, these individuals feel excited when they come in contact with distant cultures, which they feel makes the trip a good and authentic experience. Therefore, these individuals do not suffer from the so-called “cultural trauma”, which describes the inability to accept or understand the local customs and different languages, both in the “choosing a holiday” phase and during the holiday experience. That is why it can be said that cultural sensitivity can exert influence on the gap between the pre- and post-visit image.
In spite of the importance of cultural sensitivity, previous studies have focused mainly on the validation of their scales and the differences between populations, and their relationship to other concepts, with little attention being paid to tourism (Bae and Song, 2017). This is despite the fact that, today, tourists are the group in which intercultural interactions occur most frequently (He and Wei, 2014).
For this reason, and based on the works previously analysed, this research intends to discover the impact of culture on the gap in the pre- and post-visit image through cultural sensitivity. To this end, the following working hypotheses are established:
Cultural sensitivity affects the gap in the pre- and post-visit cognitive image.
Cultural sensitivity affects the gap in the pre- and post-visit affective image.
Cultural sensitivity affects the gap in the pre- and post-visit global image.
3. Methodology
The methodological procedure followed in the empirical research was based on personal surveys using a structured questionnaire as an instrument for collecting the information that filled a representative sample of tourists of both sexes and over 16 years of age who were visiting the island of Tenerife for the first time, coming from abroad and from other parts of Spain. The sample selection was made using the empirical or non-random method of quotas relative to the dimensions of nationality, sex and age, with affixation proportional to the number of tourists in each one of the dimensions established to obtain a sample similar to the population in these dimensions. The sample was obtained from the tourists who ended their stay in Tenerife and returned to their countries of origin the day after completing the questionnaire to ensure that their experience was both complete and recent. The total number of tourists that made up the sample was 411. The fieldwork was carried out in bars and cafes in and around the most popular tourist areas and attractions in Tenerife (Las Américas, Los Cristianos, Costa Adeje, El Medano, Candelaria, Puerto de la Cruz, Garachico and Los Gigantes), randomly selecting tourists during the months of June and July 2015. Table I shows the sociodemographic profile of the sample.
The measurement scales used to evaluate the different constructs of the model correspond to the following. To measure the cognitive, affective and global image gap, we have based ourselves on the works of Beerli and Martín (2004a, 2004b) and we have used a Likert scale of seven points and ten items to measure the cognitive image, of two items to measure the affective image and of one item to measure the global image. To assess the gap, the respondent indicated the extent to which each item of the cognitive, affective and global image had been better, the same or worse than was expected according to the information obtained before making the trip, on a scale going from −3 to +3, where −3 is much worse than expected, 0 is equal to expected and +3 is much better than expected. With regard to cultural sensitivity, the scale developed by Fritz et al. (2002) was used, with 13 items finally being used to assess the sensitivity level through a seven-point scale. Table II shows the final items used to measure the image gap and cultural sensitivity.
4. Results
4.1. Analysis of the validation of the measurement scales
As a preliminary step to the validation of the scale that determines the gap of the pre- and post-visit image, a frequency analysis of the items that conformed this scale was performed to analyse its distribution. The results reflect that the percentage of the negative gap (−3 to −1) is very small in all attributes of the destination (less than 5 per cent). Due to this, we have considered it more appropriate to recode the categories of −3, −2, −1 and 0 in a single state, which has been labelled “Equal to expectations or slightly worse”.
To carry out the validation of the scales, we performed a second-order confirmatory factor analysis using the AMOS software (version 22). The results of this analysis applied to the recoded scale to four states of the destination cognitive image gap determined three dimensions, which have been labelled as “Natural and Artificial Resources” (NATARTRES), “Tourism Activities” (TOURACTIV) and “Environment” (ENVIRON). To analyse the dimensionality of this scale, a new model was estimated in which all items are linked to a single factor. The results of this new model [χ2(35) = 343.02, p = 0.000, CFI = 0.76, RMSEA = 0.15] show the suitability of a multidimensional model [χ2(32) = 140.75, p = 0.000, CFI = 0.92, RMSEA = 0.09], as it presents better levels of significance and fit indexes. In fact, the analysis of χ2 differences reveals significant differences (Dif. χ2 = 202.27, Dif. g.d.l. = 3, p = 0.000). Therefore, this scale of the destination attribute gap has ultimately been formed by three dimensions.
Although the results of this measurement model indicate that it is statistically significant [χ2(32) = 140.75, p = 0.000], it should be noted that this statistic depends on the size of the sample analysed, hence the need to analyse other fit indicators. In this respect, the results obtained show that other indicators of the global fit of the model are within the values recommended by the literature (CFI = 0.92, NFI = 0.89, TLI = 0.88, RMSEA = 0.09), so that it can be concluded that the specified model accurately reproduces the observed covariance matrix. This measurement model shows an appropriate fit, as the value of CFI is higher than 0.90, although the value of RMSEA is 0.09 (Mathieu and Taylor, 2006). Following Anderson and Gerbing (1988), and as shown in Table III, the model shows acceptable individual reliability, as the relationship between each item and its respective dimension is statistically significant with higher or very close standardised regression weights in their majority at 0.7 and with values of the t statistic also significant. As for the measures of internal consistency, the values of the composite reliability (CR) of the dimensions of the gap of the cognitive image reach values higher or near 0.70 and those of the average extracted variance (AVE) exceed or are close to 0.50. Cronbach’s alpha values corroborate those obtained in CR (Table III). It can be affirmed, therefore, that the scale of the cognitive image gap is a construct of a multidimensional nature formed by three dimensions. These results indicate that the measurement model can be considered valid, although it would be advisable to replicate it in other contexts as well, and even to extend or modify the content of some of the dimensions to raise the level of reliability.
The final results of the second-order confirmatory factor analysis applied to the cultural sensitivity scale show the existence of four dimensions, which have been labelled as “Enjoyment and confidence in cultural interaction” (ENJCONFCUL), “Predisposition towards cultural interaction” (PREDISCUL), “Respect for cultural differences” (RESPCUL) and “Focusing on cultural interaction” (FOCCUL). As with the cognitive image gap scale, to analyse the discriminant validity of this scale, a new model was estimated in which all the items are linked to a single factor. The results of this new model [χ2(65) = 686.43, p = 0.000, CFI = 0.72, RMSEA = 0.15] show the suitability of a multidimensional model [χ2(61) = 274.62, p = 0.000, CFI = 0.91, RMSEA = 0.09], as it presents better levels of significance and fit indexes. In fact, the analysis of χ2differences reveals the existence of significant differences (Dif. χ2 = 411.81, Dif. g.d.l. = 4, p = 0.000).
Also, in this case, although the results of this measurement model indicate that it is statistically significant [χ2(61) = 274.62, p = 0.000], it should be noted that this statistic depends on the size of the sample analysed, hence the need to analyse other fit indicators. In this respect, the results obtained show that the other indicators of global fit of the model are within the values recommended by the literature (CFI = 0.91, NFI = 0.88, TLI = 0.88, RMSEA = 0.09), so that it can be concluded that the specified model accurately reproduces the observed covariance matrix. This measurement model shows an adequate fit, as the value of CFI is higher than 0.90 and the value of RMSEA is very close to the limit (Mathieu and Taylor, 2006). Following Anderson and Gerbing (1988), and as shown in Table IV, the model shows satisfactory individual reliability, as the relationship between each item and its respective dimension is statistically significant with standardised regression weights greater than or very close to 0.7 and with values of the t statistic also significant. As for the measures of internal consistency of the global construct and of each of the dimensions, all values of the CR indicator reach values higher than 0.70 and those of the AVE higher than 0.50. The values of Cronbach’s alpha corroborate those obtained in the composite reliability. These results indicate that the measurement model can be considered valid, although it would be advisable to replicate it in other contexts as well. Therefore, it can be affirmed that the scale of cultural sensitivity is a construct of multidimensional nature formed by four dimensions.
In Table V, the AVE values of each of the non-unidimensional constructs that are part of the model (cultural sensitivity, cognitive image gap and affective image gap) are recorded on the main diagonal, and in the remaining boxes, the squared bivariate correlations between such constructs, in addition to those corresponding to the global image gap, to test the discriminant validity. As the results show that the AVE of each construct is superior to the square of its correlation with the remaining constructs, it can be affirmed that there is discriminant validity.
4.2 Hypotheses testing
Before proceeding to contrast the hypotheses, a new variable has been created for each of the dimensions of the cognitive and affective image gap, as well as for the dimensions of cultural sensitivity, through the weighted average of the scores given by the respondents to the items that make up each dimension weighted by the regression weights of each of them in the previous CFA. These variables have been labelled with the same name given to the dimension. The results of the adjusted structural equations model are shown in Figure 1, highlighting the influence of cultural sensitivity on the image gap, whose fit is satisfactory [χ2(30) = 112.15, p = 0.000; CFI = 0.94; RMSEA = 0.08]; it is shown that cultural sensitivity affects only the global image gap (ß = 0.084, p = 0.063). Therefore, H1c is accepted and H1a (ß = 0.091 p = 0.157) and H1b (ß = −0.058 p = 0.307) are rejected. The fact that cultural sensitivity does not influence the cognitive or affective image may be a consequence of the fact that tourists with greater cultural sensitivity tend to consult a greater number of secondary sources of information before visiting the destination, thus forming an image of the destination at the most complete cognitive level that is very similar to the image they obtain while visiting the destination. On the other hand, the value of R2 for the construct of the cognitive image is relatively low because many factors, in addition to the cultural sensitivity, have an influence (e.g. the sources of information the tourists use before visiting the destination, the level of interaction they have with the destination, their motivations and their experience as tourists).
5. Conclusions, implications and limitations
In this paper, we have attempted to analyse the effect that one of the factors connected to the personal sphere of the individual exerts on the image gap, the cultural sensitivity of tourists. This is a variable that, until now, has not has been considered in the study of the image formation of a tourist destination from a personal perspective, despite the importance of cultural interactions in the context of tourism and it being an internal factor that influences tourist behaviour, being that the adaptability of tourists to the culture of the destination is influenced by their cultural sensitivity.
The results of this work reflect that the cultural sensitivity of tourists directly and positively influences the gap in the global image of the destination, so the more cultural sensitivity an individual has, the better the overall image of the place they will have after their visit in comparison to the image they had before visiting the destination. This shows that tourists with a high level of cultural sensitivity are encouraged to come into contact with other cultures, which leads them to have an experience at the destination that improves the post-visit global image. However, cultural sensitivity does not influence the cognitive or affective image change, which may be due to the fact that, here, other factors, such as the amount of secondary information obtained by the tourists before visiting the destination or even the level of interaction they have had with the destination, have an effect. It may be the case that tourists with high level of cultural sensitivity obtain a lot of information about the destination before visiting that leads them to have a pre-visit image, which is very complete and quite similar to the post-visit image. On the other hand, the opposite may also be true, whereby tourists with low cultural sensitivity, who barely search for any information beforehand and focus on rest and relaxation at “sun, sea and sand” destination, do not produce a change in the cognitive or affective image as their simple requirements are largely met.
The results of this work represent an advance in the literature, as:
the topic of cultural sensitivity has hardly received any attention in the literature of tourism marketing;
there are few studies that have verified the effect of culture on the image of a destination and even less in the tourism sector (Karroubi, 2014); and
there are no studies that have studied the influence of cultural sensitivity on the gap in the image of a tourist destination.
This research has attempted to contribute towards a greater knowledge in the field of tourist destination image and, more specifically, on the role of cultural sensitivity in post-visit image formation, as much in the professional sphere as the academic. From an academic point of view, an attempt has been made to provide evidence of the influence of cultural sensitivity on the image gap in tourist destinations, which, given the small amount of empirical evidence on the subject, contributes to a better understanding of how the personal factors of tourists influence the process of image evolution by further expanding knowledge on the topic of tourist destination image. Likewise, the validation of a scarcely studied and applied scale in the tourism sector can also be considered as a contribution. From a practical point of view, the results of this research have implications for the professional sector. The success of business in the twenty-first century will depend on how individuals and organisations acquire and practice cross-cultural sensitivity and the ability to deal with individuals from different cultures and places of origin (Harris, 2004), especially in a sector such as that of tourism, formed by individuals who come from many different cultures. Along this same line, some authors affirm that it is not enough simply to make correct translations of the promotional material, but that it is also necessary to adapt it to different cultural sensibilities to facilitate the processing of information and to obtain more favourable attitudes towards the products or services that the destination offers (Luna et al., 2002) – in other words, to personalise the content (Singh et al., 2006; Tixier, 2005). Moreover, cultural sensitivity may be a good criterion of segmentation that would allow the institutions responsible for the marketing of destinations to adapt their marketing strategies to segments with different cultural sensitivities, as there are differences in the change in perception of global image that occurs before and after the visit.
Although we have attempted to carry out a research work following criteria of scientific rigor, with the objective of providing empirical evidence that contributes to a greater knowledge and understanding of the process of image gap formation that occurs for tourist destinations, we are aware of some limitations, both conceptual and methodological. From a conceptual point of view, the research is limited to the context of its own objectives and, in addition to culture, there are other factors that influence the change in the perceived image of tourist destinations that have not been included in the present research but may also affect the process, such as variables typical of the information search process or other personal factors of tourists. Also, the role that culture plays in the gap could be further explored, as this work has focused on cultural sensitivity without considering other factors that could potentially be studied to better explain the image gap (for example, geographical distance). Likewise, it would be interesting to study, in greater depth, tourist behaviour before and during a stay at a tourist destination in relation to their level of cultural sensitivity, since those with a high level of cultural sensitivity may constitute an attractive market segment that requires the design of strategies and actions of differentiation that satisfy their specific needs. From a methodological perspective, this work, like any other empirical research, presents limitations that affect the generalisation of its results, as the scope of the investigation only permits the results of the analyses to be applied to the population from which the sample comes and to the tourist destination of Tenerife. It would therefore be advisable to replicate this research at other destinations.
Sociodemographic profile of the sample
| Characteristics | N | (%) |
|---|---|---|
| Gender | ||
| Male | 199 | 48.4 |
| Female | 212 | 51.6 |
| Age | ||
| 16-24 years | 32 | 7.8 |
| 25-34 years | 106 | 25.8 |
| 35-44 years | 62 | 15.1 |
| 45-54 years | 80 | 19.5 |
| 55-64 years | 81 | 19.7 |
| More than 64 years | 50 | 12.2 |
| Level of education | ||
| No formal qualifications | 8 | 1.9 |
| High school diploma | 42 | 10.2 |
| High school advanced level | 196 | 47.7 |
| Standard university degree | 127 | 30.9 |
| Master’s degree/Phd | 37 | 9.0 |
| Social class | ||
| Upper | 38 | 9.2 |
| Upper-middle | 78 | 19.0 |
| Middle | 135 | 32.8 |
| Lower-middle | 98 | 23.8 |
| Working | 4 | 1.0 |
| Nationality | ||
| German | 54 | 13.1 |
| British/Northern Irish | 135 | 32.8 |
| Spanish | 65 | 15.8 |
| Scandinavian (Swedish, Norwegian, etc.) | 52 | 12.7 |
| Other | 105 | 25.5 |
Definitive items of the measurement scales
| Dimensions | Code | Items |
|---|---|---|
| Cognitive image | ||
| Natural and artificial resources | NAR1 | Climate |
| NAR2 | Natural resources (countryside, national parks, flora and fauna, …) | |
| NAR3 | Tourism infrastructure (hotels, restaurants, shopping centres, golf courses, …) | |
| NAR4 | General infrastructure (highways, airports, public transport links, sanitation, internet, …) | |
| Tourist activities | TOURAC1 | Leisure activities (theme parks and water parks, guided tours, golf courses, wellness centres and spas, …) |
| TOURAC2 | Nightlife (bars, night clubs, pubs, casinos, …) | |
| TOURAC3 | Adventure activities (skydiving, scuba diving, rafting, …) | |
| TOURAC4 | Sporting activities (sailing, windsurfing, cycling, CrossFit, …) | |
| Environment | ENV1 | Environment (cleanliness, clean air, …) |
| ENV2 | Security | |
| Affective image | ||
| AFFEC1 | Pleasant location | |
| AFFEC2 | Entertaining, exciting and fun | |
| Cultural sensitivity | ||
| Enjoyment and confidence in cross-cultural interaction | ENJCON1 | I love interacting with people from different cultures |
| ENJCON2 | I feel self-confident when I interact with people from other cultures | |
| ENJCON3 | I always know what to say when I interact with people from other cultures | |
| ENJCON4 | I am very sociable with people from other cultures | |
| ENJCON5 | I feel safe and secure when I interact with people from other cultures | |
| Predisposition towards cross-cultural interaction | PREDIS1 | I tend to get discouraged from interacting with people from other cultures |
| PREDIS2 | I dislike being with people from other cultures | |
| PREDIS3 | I tend to get discouraged from interacting with people from other cultures | |
| Respect for different cultures | RESP1 | I respect the values of people from other cultures |
| RESP2 | I respect the modes of behaviour and customs of people from other cultures | |
| Focus on cross-cultural interaction | FOCC1 | I am open minded towards people from other cultures |
| FOCC2 | I am very observant when interacting with people from other cultures | |
| FOCC3 | I enjoy the cultural differences when I interact with people from other cultures | |
Confirmatory factor analysis of the scale of the cognitive and affective image gap
| Causal relationships | Standardised estimators | t | p | Internal consistencya |
|---|---|---|---|---|
| NATARTRES ← COGIMGAP | 0.958 | CR = 0.818 |
||
| TOURACTIV ← COGIMGAP | 0.614 | 5.704 | 0.000 | |
| ENVIRON ← COGIMGAP | 0.726 | 6.009 | 0.000 | |
| NAR1 ← NATARTRES | 0.536 | CR = 0.726 |
||
| NAR2 ← NATARTRES | 0.672 | 8.877 | 0.000 | |
| NAR3 ← NATARTRES | 0.660 | 8.803 | 0.000 | |
| NAR4 ← NATARTRES | 0.655 | 8.769 | 0.000 | |
| TOURAC1 ← TOURACTIV | 0.604 | 9.712 | 0.000 | CR = 0.811 |
| TOURAC2 ← TOURACTIV | 0.591 | |||
| TOURAC3 ← TOURACTIV | 0.824 | 11.774 | 0.000 | |
| TOURAC4 ← TOURACTIV | 0.837 | 11.832 | 0.000 | |
| ENV1 ← ENVIRON | 0.728 | CR = 0.643 |
||
| ENV2 ← ENVIRON | 0.648 | 8.257 | 0.000 | |
| AFFEC1 ← AFFEIMGAP | 0.675 | CR = 0.697 |
||
| AFFEC2 ← AFFEIMGAP | 0.786 | 9.643 | 0.000 |
CR: composite reliability; AVE: average variance extracted; α: Cronbach’s alfa
Confirmatory factor analysis of the scale of cultural sensitivity
| Causal relationships | Standardised estimators | t | p | Internal consistencya |
|---|---|---|---|---|
| ENJCONFCUL ← CULTSENSIT | 0.754 | CR = 0.863 |
||
| PRESDISCUL ← CULTSENSIT | 0.563 | 7.888 | 0.000 | |
| RESPCUL ← CULTSENSIT | 0.779 | 10.802 | 0.000 | |
| FOCCUL ← CULTSENSIT | 0.997 | 10.724 | 0.000 | |
| ENJCON1 ← ENJCONFCUL | 0.713 | 13.953 | 0.000 | CR = 0.841 |
| ENJCON2 ← ENJCONFCUL | 0.746 | 14.618 | 0.000 | |
| ENJCON3 ← ENJCONFCUL | 0.651 | 12.685 | 0.000 | |
| ENJCON4 ← ENJCONFCUL | 0.765 | |||
| ENJCON5 ← ENJCONFCUL | 0.710 | 13.882 | 0.000 | |
| PREDIS1 ← PREDISCUL | 0.749 | CR = 0.780 |
||
| PREDIS2 ← PREDISCUL | 0.770 | 12.460 | 0.000 | |
| PREDIS3 ← PREDISCUL | 0.687 | 11.807 | 0.000 | |
| RESP1 ← RESPCUL | 0.878 | CR = 0.772 |
||
| RESP2 ← RESPCUL | 0.701 | 12.348 | 0.000 | |
| FOCC1 ← FOCCUL | 0.771 | CR = 0.757 |
||
| FOCC2 ← FOCCUL | 0.646 | 12.337 | 0.000 | |
| FOCC3 ← FOCCUL | 0.720 | 13.779 | 0.000 |
CR: composite reliability; AVE: average variance extracted; α: Cronbach’s alfa
Discriminant validity
| Constructs | (1) | (2) | (3) | (4) |
|---|---|---|---|---|
| CULTSENSIT (1) | 0.863 | |||
| COGIMGAP (2) | 0.004 | 0.607 | ||
| AFFEIMGAP (3) | 0.000 | 0.295 | 0.537 | |
| GLOBIMGAP (4) | 0.008 | 0.261 | 0.375 | – |
Note: The italic elements are the values of AVE and the remaining elements are the correlations squared between the constructs
© Asunción Beerli-Palacio and Josefa D. Martin-Santana. This work is published under https://creativecommons.org/licenses/by-nc/3.0/legalcode (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.