Examining How Country Image Influences Destination Image in a Behavioral Intentions Model: The Cases of Lloret De Mar (Spain) and Cancun (Mexico)

ABSTRACT Understanding the importance of a country’s image in the behavioral intentions of tourists is essential for sun-and-sand destinations. This study examines an integrated model of behavioral intentions regarding two international tourist destinations, namely Cancun (Mexico) and Lloret de Mar (Spain). The results indicate that country image influences destination image; destination image influences value, satisfaction, and behavioral intentions; value influences satisfaction; and satisfaction influences behavioral intentions. These findings confirm that the country and destination images are different constructs, and that destination image is the key to attracting tourists. Additionally, there are some differences in the relationships hypothesized in the model among the destinations.


INTRODUCTION
Tourism destinations need to increase tourists' loyalty by developing strategies to obtain long-term relationships (Yoon & Uysal, 2005) and improve revenue, employment, and regional development (Chen & Tsai, 2007). Identifying the antecedents of loyalty is especially important in destinations whose main products are sun and sand, where tourist loyalty becomes a relevant aspect of management since these destinations are characterized by the need for a high number of repeat tourists (Alegre & Cladera, 2006). This occurs in different typologies of destinations with different characteristics and service offers such as those of second and third generation (Knowles & Curtis, 1999), although there are no studies that have compared loyalty models of destinations in these two categories.
On the other hand, there is very little research facilitating understanding of the country image as a determinant of the destination image in behavioral intention models. Literature on the effect of a country's image or the effect of the country of origin on consumers' evaluations has been numerous and diverse in recent years (Knight & Calantone, 2000;Laroche, Papadopoulos, Heslop, & Mourali, 2005;Roth & Diamantopoulos, 2009). Nevertheless, there is not much research relating country of origin or country image to tourism destination image. It includes a theoretical study without empirical evidence in which the authors integrate country image and destination image (Mossberg & Kleppe, 2005), and a study that identifies the influence of country image on the image of the tourism destination among international tourists visiting Nepal (Nadeau, Heslop, O'Reilly, & Luk, 2008). However, these studies fail because they do not separate sufficiently the two constructs, country image and destination image, which are significantly different, as indicated by Campo and Álvarez (2010), Lee and Lockshin (2012), and Zhou, Murray, and Zang, (2002). Moreover, the marketing literature has shown that the general image of a country is distinct from that of the products associated with that country (Pappu, Quester, & Cooksey, 2007). In tourism, the tourist destination is the product for the tourist, since the destination is an amalgam of individual products that combine to form the total experience of the result of the visit (Murphy, Pritchard, & Smith, 2000).
Consequently, it is necessary to look more closely at the drivers leading to the behavioral intentions of sun-and-sand tourists, of both second and third generations, focusing especially on the influence of country image on destination image, as well as their interrelationships with value and satisfaction. Most of these relationships have been proved by the literature in a fragmentary and partial manner. Therefore and given the scarcity of studies developing causal models among the variables proposed in only one model, the objectives of this study are twofold. Firstly, to incorporate country image into a model of antecedents of behavioral intentions with simultaneous relationships between country image, destination image, value, satisfaction, and behavioral intentions. Secondly, to test the proposed relationships in second-and third-generation destinations.

THEORETICAL FOUNDATION AND RESEARCH HYPOTHESES
The conceptual model of this research is founded on the three components of attitude: cognitive, affective, and conative. Thus we proceed on the basis of the reformulation of attitude theory by Bagozzi (1992), in which he postulates that cognitive appraisal precipitates emotions and that these emotions influence an individual's behavior. This behavior is represented by a sequential process of cognitive, affective, and conative factors. This sequential process is represented firstly in the conceptual model by a cognitive component formed by two "country image dimensions", namely people and country character and destination image and value. Secondly, an affective component formed by "satisfaction" and thirdly, by behavioral intentions. The relationships between the constructs have been argued and justified in the following. Figure 1 displays the conceptual model and its relationships used in this study.
Country image literature's point of departure is studies on product-country-image (PCI) or country of origin (COO). These studies related to the image consumers have of a country's products (Maher & Carter, 2011;Papadopoulos & Heslop, 2003). PCI researchers have studied three types of effects on consumers: cognitive, affective, and normative (Van Ittersum, Candel, & Meulenberg, 2003). Studies on cognitive effects focused on finding out if influence on consumer's perception is due to a halo effect, a summary effect, a default heuristic model, or the cognitive elaboration process (Brijs, Bloemer, & Kasper, 2011). The halo effect appears when the consumer is not very familiar with a product, producing an influence of country image on beliefs associated with the product. Those beliefs influence attitudes, operating the national stereotypes, as a halo, permitting the evaluation of these country's products (Han, 1989). Knight and Calantone (2000) reformulate the halo effect and the summary models proposing that beliefs and country image have a direct influence on the attitude toward imported product. Manrai, Lascu, and Manrai (1998) developed an intermediate model of influence over intentions denominated the default heuristic produced when the consumer is moderately familiar with the product; in this case, beliefs multiply the effects of country image in attitudes. Regarding the cognitive elaboration process, Hadjimarcou and Yu (1999) found that country-of-origin information can result in the use of category-and stereotype-based heuristics. On the other hand, the other two types of studies about PCI hold that affection and admiration for a given country influence evaluations of and attitudes toward products (affective studies; Batra, Ramaswamy, Alden, Steenkamp, & Ramachander, 2000), and normative studies analyze consumer relations with foreign products and how product's source country relates to his inner norms and values (Brijs et al., 2011).
Research into PCI has been incorporating studies analyzing how the perception of a country and its inhabitants influences consumers' attitude toward the products of this country (Heslop, Papadopoulos, Dowdles, Wall, & Compeau, 2004;Laroche et al., 2005;Maher & Carter, 2011), and these studies were based on construct operationalization using the components "cognitive" (beliefs or knowledge regarding the country and its products), "affective" (the feelings toward the country and its products), and "conative" (behavioral intentions regarding its products) (Laroche et al., 2005;Wang, Li, Barnes, & Ahn, 2012). These three components have also been used in tourism country image studies (Campo & Álvarez, 2014;Sönmez & Sirakaya, 2002), taking into consideration that attitude, in the case of a tourist, describes positive or negative evaluations when a consumer shows certain types of behavior which predispose him or her to take action (Azjen, 1991).
Research into tourism has developed models relating to country image using other tourist constructs to explain tourists' attitudes and intentions regarding a country's image (Kim & Morrsion, 2005;Nadeau et al., 2008). Recent literature analyzing tourists' post purchase behavior has used the three components (i.e. cognitive, affective, and conative) in order to produce models relating country image to other tourist variables (Elliot, Papadopoulos, & Kim, 2011;Nadeau et al., 2008) in which the cognitive element is the attitude formation, the affective element is a response showing tourists' preferences, and the conative element is a behavioral intention indication shown by the tourist and associated with a tourism destination (Lee, 2009). Nadeau et al. (2008) developed a model connecting country image and destination image and integrating, in a single construct, the components "cognitive" and "affective" of destination image following other studies like that of Kim and Yoon (2003). These authors explained the cognitive part using country image dimensions, while other authors (Chen & Phou, 2013) consider destination image as a cognitive component of tourists' attitude. Following these criteria, this study develops the first model's component, i.e. cognitive, using two dimensions from country image, namely country character and people character. Country character is defined as the tourist's beliefs regarding the country, and people character is defined as the tourist's beliefs regarding its inhabitants (Nadeau et al., 2008).
Very few studies of tourism include the country image in models of behavioral intentions, and the influence of country image on destination image. Mossberg and Kleppe (2005) developed a theoretical model using this relationship, but did not test it empirically. Elliot et al. (2011) developed an integrated model of country and destination image in which they found positive influences among cognitive variables of country image and destination and product beliefs, but the sample was made up of South Korean people attending an event. It is not an analysis of immediate post-purchase tourist behavior of tourists who recently visited their destinations. Nadeau et al. (2008) developed a model that places the emphasis on the relationship between country and destination image within the broader country image context. They use the country and people character dimensions, defined as the tourist's beliefs regarding the country and its inhabitants, and identify a positive and direct relationship of people character and country character with destination image. Therefore, based on the relationship established in the research cited above, and the paucity of studies, the following hypotheses (Hs) are proposed: H1: People character has a direct and positive effect on destination image.
H2: Country character has a direct and positive effect on destination image.
Although there is no consensus regarding the definition of destination image, we could define it as the sum of a person's beliefs, ideas, and impressions concerning a tourism destination (Crompton, 1979), consisting of numerous elements ranging from the functional to the psychological (Gallarza, Gil Saura, & Calderón García, 2002). Consequently, destination image is associated with a subjective interpretation of tourists' feelings and beliefs regarding a specific destination (Baloglu & McCleary, 1999), and is a key determinant influencing tourists' attitudes toward a destination (Yoon & Uysal, 2005).
Most studies of destination image show differences in the conceptualization and definition of its dimensions (Tasci, Gartner, & Cavusgil, 2007); in the attributes configuring the construct (Prayag & Ryan, 2012); and in the methodologies of measurement (Gallarza et al., 2002). Some authors use one cognitive dimension (Bigné, Sánchez, & Sanz, 2009), some of them use various cognitive dimensions (Chi & Qu, 2008), or measure it on the basis of functional and psychological characteristics (Prayag & Ryan, 2012). However, Baloglu and McCleary (1999) assert that to determine the destination's overall image a combination of cognitive and affective dimensions is necessary, while others consider that it is a multidimensional construct composed of the previously mentioned two dimensions and the conative dimension (Beerli & Martín, 2004). The cognitive dimension denotes beliefs and knowledge regarding the tourist destination; the affective dimension implies the evaluation of the feelings a tourist has toward a given tourist destination; the conative dimension is the manifestation/ intention of a tourist's behavior at the destination (Zhang, Fu, Cai, & Lu, 2014). For this reason, other authors developed models in which the destination image has a cognitive component as well as an affective one, but with no other affective constructs in the model (Beerli & Martín, 2004;Mackay & Fesenmaier, 2000;Qu, Kim, & Im, 2011). Therefore, for this study and following the aforementioned criteria, the second cognitive component of the model is destination image.
Despite the differences in the above mentioned measurements of the construct, the tourism literature has proved the direct and positive relationships of destination image, without the country image construct, with (1) value (Kim et al., 2013), (2) satisfaction (Wang & Hsu, 2010), and (3) behavioral intentions (Correria Loureiro & Miranda González, 2008). Thus, based on these previous findings, and the absence of these relationships in the models including country image, the following hypotheses are formulated: H3: Destination image has a direct and positive effect on value.
H4: Destination image has a direct and positive effect on satisfaction.
H5: Destination image has a direct and positive effect on behavioral intentions.
Customer value refers to a consumer's overall evaluation of the difference between perceived benefits and sacrifices in a specific transaction (Zeithaml, 1988). However, there are different opinions regarding the cognitive nature of value versus its affective nature. Some researchers argue the cognitive dimension of value (Zeithaml, 1988), while others defend the presence of both cognitive and affective dimensions (Sweeney & Soutar, 2001). The cognitive dimension has also been measured by means of one-dimensional and multidimensional scales (Forgas-Coll, Palau-Saumell, Sánchez-García, & Caplliure-Giner, 2014). For the purpose of this study, the onedimensional scale proved adequate (Phillips et al., 2013), considering as in other studies (Baloglu & Mangaloglu, 2001), a variable belonging to the cognitive component of destination image.
Studies in the tourism context have suggested relationships between value and satisfaction (Bonnefoy-Claudet & Ghantous, 2013), and between customer value and behavioral intentions (Chen & Chen, 2010;Chen & Tsai, 2008). Therefore, based on the empirical studies in different tourist contexts, the following is hypothesized: H6: Customer value has a direct and positive influence on satisfaction.
H7: Customer value has a direct and positive influence on behavioral intentions.
Oliver's (1980) expectancy disconfirmation paradigm considers satisfaction to be the result of comparing the initial expectations with the perceived yield in the consumption of a product or service (Oliver, 1980). Satisfied tourists have a higher propensity to revisit the tourist destination and recommend it to relatives and friends (Chi & Qu, 2008). Bitner and Hubbert (1994) identified two types of satisfaction in consumer behavior: (1) transaction-specific, that is, the satisfaction with a specific service encounter; (2) overall satisfaction, that is, a cumulative construct summing satisfaction and various facets of the destination (Prayag & Ryan, 2012). The overall satisfaction perspective is adopted in this study because a tourist's satisfaction is not limited to satisfaction with a specific product or service (Tian-Cole & Cromption, 2003), but consists of an overall evaluation of his or her consumption experience (Johnson, Anderson, & Fornell, 1995) from leaving home until his or her return (Ritchie & Crouch, 2005) from a tourist destination (Chen & Tsai, 2007).
The literature has found, at the transaction level, that visitor satisfaction is affective (Tian-Cole & Cromption, 2003), and following the theoretical foundation of this study, that satisfaction is the affective component of the model. Hence, the more satisfied a tourist is, the higher the likelihood of revisiting the destination and recommending it to friends and relatives (Sun et al., 2013). Satisfaction positively affects tourists' behavioral intentions at tourist destinations (Chen & Chen, 2010;Chen & Tsai, 2007;Chi & Qu, 2008;Forgas-Coll, Palau-Saumell, Sánchez-García, & Callarisa-Fiol, 2012;Prayag, 2009). Therefore, based on these previous findings, the following is hypothesized: H8: Satisfaction has a direct and positive effect on behavioral intentions.
A broadly accepted definition of loyalty is Oliver's (1999), who defines it as the highest level of commitment, implying the transition from a favorable predisposition toward a product to a repeat purchase commitment. In tourism the loyalty of a tourist to a tourist destination has been treated as an extension of the loyalty of a consumer to a product because the tourist experience is considered to be a product (Yoon & Uysal, 2005). Jacoby and Chestnut (1978) distinguish between behavioral, attitudinal, and composite loyalty. Behavioral loyalty analyzes the results of behavior such as repeat visits. Attitudinal loyalty refers to tourist intentions to recommend or repeat visit a destination. Composite loyalty integrates behavioral and attitudinal loyalty (Oppermann, 2000). However, at the operational level, in most studies tourism literature has used attitudinal loyalty, so-called behavioral intentions (Chen & Chen, 2010;Ha & Jang, 2010), using items such as repurchase intentions, recommendations, and speaking positively to friends and relatives (Žabkar, Brenčič, & Dmitrović, 2010): (1) repurchase intention, that is, the individual's judgment regarding buying a designated service again from the same company (Hellier, Geursen, Carr, & Rickard, 2003); (2) willingness to recommend reflects a positive behavioral intention, which is the result of the value of the experiences enjoyed in the consumption of a service (Bowen & Shoemaker, 2003); (3) word-of-mouth is seen by people as reliable information coming from others who have already had a previous experience (Ha & Jang, 2010). Consequently, behavioral intentions are the model's conative components which we propose to analyze.

METHODOLOGY Survey Instrument
The survey instrument was a structured questionnaire that used a 5-point Likert scale where "1" indicates "strongly disagree" and "5" indicates "strongly agree". The questions were based on a literature review.
This study has followed the criterion of measuring country and destination image by means of cognitive variables, since affective and conative variables are in other separate constructs of the proposed model, such as satisfaction, and behavioral intentions. Taking the above into account, in order to measure the country image two dimensions were operationalized based on the definitions of people character and country character used in this study. The items of these dimensions were adapted from Nadeau et al. (2008). The measurement of destination image includes items adapted from Prayag and Ryan (2012).
Customer value is operationalized, as in other studies in the marketing literature, using a scale which tries to measure overall customer value in terms of "value for money" (Chen & Tsai, 2008), and with items taken from Sirdeshmukh, Singh, and Sabol (2002).
In relation to satisfaction, and as has been mentioned above, the overall satisfaction perspective is adopted in this study, and was measured using items from Forgas-Coll et al. (2012). Behavioral intentions measures were adapted from Lee (2009).
The questionnaire was divided into the following three sections: (1) In order to ensure that the tourists surveyed had well-founded criteria regarding the country image, they were asked if they knew other destinations in the country. Specifically they were asked a discriminatory question: "Have you visited during your stay or on previous trips other tourism destinations in the country?" Only tourists who responded "Yes'" to this question continued in the survey; (2) country image, destination image, value, satisfaction, and behavioral intentions; (3) sociodemographic information.
All items used in the questionnaire were submitted to a panel of 10 experts in destination management in both countries, five for each 954 JOURNAL OF TRAVEL & TOURISM MARKETING country, to ensure the items were an adequate and thorough representation of the constructs under investigation. The first draft of the questionnaire was tested with a pretest of 50 questionnaires to assess the items used in the survey instrument to further examine the content validity, reliability, and comprehension. Suggested changes and improvements were minor, and they were primarily related to wording clarifications.

Site
The research was carried out in two sun-andsand tourist destinations: Lloret de Mar (Catalonia, Spain) and Cancun (Quintana Roo, Mexico). We chose two tourist destinations from two different countries, a developed one (Spain) and a developing one (Mexico) to identify the potential differences in the relationships proposed in the model. In addition, these ountries were selected because both are second-and third-generation destinations according to Knowles and Curtis' (1999) typology, in which these authors define the differences between tourist destinations.
The first generation of tourist destinations were those on the south coast of England, United Kingdom (UK), developed in the Victorian era, with Victorian buildings, excellent hotels, and public facilities, which were the foundation of their success. Those destinations had easy access by train and car and were consolidated between 1930 and 1960, not showing signs of stagnation or decline until the end of the 1960s because of the popularization of air transport and holidays abroad.
The second generation of tourist destinations appears in Europe in the late 1960s thanks to tour operators' ability to attract tourists from North and Central Europe to yearround sun and beach destinations on the Mediterranean coast. These destinations are characterized by the rapid development of infrastructure, easy access by air transport, and overcrowding. These destinations are based on the lack of differentiation and high standardization of products and services (Knowles & Curtis, 1999).
The third generation of tourist destinations were developed in the late 1980s, predominantly in the developing world (Dubai in the United Arab Emirates, Cancun in Mexico, the Maldives), and are planned destinations that provide first-rate accommodation, nearly all of it in hotels with at least four stars, and always adding an exotic touch (Russo & Segre, 2009). These third generation destinations are characterized by a high density of hotel places, a great dependence on tour operators, a combination of luxury facilities and exotic scenarios for a vast number of tourists coming from all over the world (Knowles & Curtis, 1999), and also emerging imbalances which, in the case of Cancun, leads to an explosive urban development, lack of public services, low agricultural productivity, and environmental degradation.
Lloret de Mar is a town 80 km north of Barcelona, which became a second-generation tourist destination in the late 1950s. It has 29,727 hotel beds located within the city, and is visited by 954,507 tourists a year, of whom 80% are international, French and Russian tourism being the most important markets in 2012 (Lloret Tourism, 2013). Cancun (Quintana Roo, Mexico) is a third-generation destination, planned and built for tourism use from 1975 onwards, and is located on the northeast coast of the Yucatán Peninsula, 1600 km south of Mexico Distrito Federal (DF). It has 60,000 hotel beds (Sectur, 2013), located in the hotel zone, and is visited by 4,093,942 tourists, 60% of whom are international (Sedetur, 2014), Americans and Canadians being the most important markets (Sectur, 2013).
The two-destinations comparison was undertaken to enable a more in-depth testing of the model and to identify the differences between second-and third-generation -tourist destinations between the causal relationships of the structural model.

Sampling and Data Collection
A convenience sampling strategy was employed, gathering a total of 1228 questionnaires from international tourists older than 18 years, between the months of July and August 2011 (Lloret de Mar) and in January 2012 (Cancun). The difference in dates is due to differences in the seasonality of the destinations. Of the total number of questionnaires, 22 were rejected as incomplete, a total of 1206 being accepted: 599 in Lloret de Mar and 607 in Cancun. 48% of the total number of participants were men and 52% women. Age distribution was as follows: 18-24 years old (16%), 25-34 years old (21%), 35-44 years old (23%), 45-54 years old (25%), 55-64 years old (11%), and 65 years old or over (4%). As to education, 53% of participants held university degrees. With regard to tourist destinations, the demographic proportions of the total sample were reasonably maintained. As regards nationality, 75% of the Lloret de Mar respondents were French and Russian, while 63% of the respondents in Cancun were from the United States (US) and Canada.

Method of Analysis
H1-H8 were tested by means of structural equation models (SEM). The models were estimated from the matrices of variances and covariances by the maximum likelihood procedure with EQS 6.1 statistical software (Bentler, 2006).

Validation of Scale
The first analysis focused on the study of the psychometrical properties of the model for the whole sample. As can be observed in Table 1 (confirmatory factor analysis (CFA)), the goodness-of-fit indices of the proposed model showed a good fit to the data (Chi-squared (χ2) = 163.701, df = 155, p = 0.300, root mean square error of approximation (RMSEA) = 0.016, comparative fit index (CFI) = 0.998, non-normed fit index (NNFI) = 0.995) (Jöreskog & Sörbom, 1996). The convergent validity is demonstrated because the factor loadings are significant and greater than 0.5 (see Table 1) (Bagozzi & Yi, 1988;Hair, Black, Babin, Anderson, & Tatham, 2006), and because the average variance extracted (AVE) for each of the factors is higher than 0.5 (Fornell & Larcker, 1981) (see Table 1). Table 2 shows the discriminant validity of the constructs considered, evaluated through AVE (Fornell & Larcker, 1981). The square roots of the AVE are greater than the correlations among the constructs, supporting the discriminant validity of the constructs.

Structural Models Results
The overall structural model showed a good fit to the data, given that the probability of the χ 2 is higher than 0.05 (0.384), CFI is close to unity (0.997), and RMSEA is close to 0 (0.018). Additionally, the variance in the destination image (R 2 = 0.54) is explained by the people and country character; the variance in value (R 2 = 0.50) can be attributed to the destination image; the variance in satisfaction (R 2 = 0.80) is explained by the destination image and value, and the variance in behavioral intentions (R 2 = 0.71) is explained by the destination image and satisfaction, indicating that the model of this study permits us to predict and explain behavioral intentions.
On the other hand, the structural models of Lloret de Mar and Cancun showed a good fit to the data, given that the probability of the χ 2 is higher than 0.05 (0.086 and 0.093), CFI is close to unity (0.993 and 0.995), and RMSEA is close to 0 (0.019 and 0.021). Additionally, the variance in the destination image is explained by the people character in Lloret de Mar (R 2 = 0.53), and people and country character in Cancun (R 2 = 0.39); the variance in value can be attributed to the destination image in Lloret de Mar (R 2 = 0.55) and in Cancun (R 2 = 0.37); the variance in satisfaction is explained by the destination image and value in Lloret de Mar (R 2 = 0.85) and in Cancun (R 2 = 0.70), and the variance in behavioral intentions is explained by the destination image and satisfaction in Lloret de Mar (R 2 = 0.76), and by satisfaction in Cancun (R 2 = 0.72), indicating that the model of this The analysis shows that seven of the eight relationships proposed in the model are accepted for the sample as a whole (Table 3 and Figure 2). The direct and positive effects of people character on destination image are supported (γ 11 = 0.68, t-value = 11.02), as are those of country character on destination image (γ 12 = 0.10, t-value = 2.18); of destination image on value (β 21 = 0.71, t-value = 13.44), on satisfaction (β 31 = 0.49, t-value = 9.30), and on behavioral intentions (β 41 = 0.15, t-value = 2.54); of value on satisfaction (β 32 = 0.48, t-value = 9.92), and of satisfaction on behavioral intentions (β 43 = 0.72, t-value = 11.03). Thus, H1-H6, and H8 were supported. The only hypothesis that was not supported (H7) pointed to no significant relationship between value and behavioral intentions (β 42 = 0.01, t-value = 0.15).
The next stage of the analysis was to examine the inferred causal relationships between behavioral intentions and their predictors in each of the destinations studied.
The results of Lloret de Mar and Cancun are shown in Table 4, and Figures 3 and 4. The paths of Lloret de Mar are relatively stronger than in Cancun, confirming similar results of the sample as a whole in the relationships of   people character to destination image (γ 11 = 0.68, t-value = 6.33), of destination image to value (β 21 = 0.74, t-value = 10.84), to satisfaction (β 31 = 0.52, t-value = 7.07), and to behavioral intentions (β 41 = 0.10, t-value = 1.98), of value to satisfaction (β 32 = 0.47, t-value = 6.94), and of satisfaction to behavioral intentions (β 43 = 0.73, t-value = 6.08). However, unlike the sample as a whole, country character does not have a significant influence on destination image (γ 12 = 0.08, t-value = 0.86). Additionally, the relationship between value and behavioral intentions is not significant as in the case of the total sample (β 43 = 0.06, t-value = 0.72).
The paths of Cancun also confirm similar results of the sample as a whole in the relationships of people character and country character to destination image (γ 11 = 0.50, t-value = 5.1; γ 12 = 0.19, t-value = 2.89), of destination image to value (β 21 = 0.61, t-value = 7.23) and to satisfaction (β 31 = 0.50, t-value = 4.84), of value to satisfaction (β 32 = 0.43, t-value = 4.27), and of satisfaction to behavioral intentions (β 43 = 0.72, t-value = 5.43). However, unlike the sample as a whole, destination image does not have a significant influence on behavioral intentions (β 41 = 0.03, t-value = 0.23). Neither in Cancun nor Lloret de Mar is the relationship between value and behavioral intentions significant (β 43 = 0.09, t-value = 0.78).

DISCUSSION AND CONCLUSION
This research aimed to demonstrate that country image, destination image, value, and satisfaction were important predictors of behavioral  intentions regarding sun-and-sand destinations. It has also demonstrated that significant differences exist in tourists' perception between second-and third-generation destinations. Based on these results it is believed that the destination behavioral intentions model outlined in the conceptual framework is corroborated. These relationships between constructs have been studied habitually by the literature, but generally in a partial or fragmentary way. Consequently, this study contributes to increasing knowledge of tourist behavior in sun-and-sand destinations. This study extends behavioral intentions literature to investigate key consequences of country image and destination image as two separate constructs, influencing antecedents of behavioral intentions through variables such as value and satisfaction, and it can also be applied to an integration research framework in a country image and destination image context. These findings contribute to the theoretical literature of destination behavioral intentions because previous research does not include satisfaction as an affective variable (Elliot et al., 2011) or does not discriminate between value and satisfaction in different constructs (Nadeau et al., 2008). In addition, this study confirms Bagozzi's (1992) contributions in which the cognitive evaluation of an individual has an affective response and the affective response has a behavioral response.
The results of the study confirm that country image and destination image are two different constructs (Campo & Álvarez, 2010). It is confirmed that country image is an antecedent of destination image, as suggested previously by Nadeau et al. (2008) and Elliot et al. (2011). Nevertheless, the results of this study, unlike the one mentioned (Nadeau et al., 2008), show a stronger relationship between people character and destination image than between country character and destination image, suggesting that, for sun-and-sand tourists at the two destinations analyzed, contact with the local population is much more important than the technical and political development of the country in their perception of the destination image. These results could suggest a certain halo effect (Han, 1989) of country image in the beliefs and attributes of the destination because the country image is the factor influencing the evaluation of tourist destinations because country image is the factor influencing the evaluation of tourist destinations.
The direct relationships of destination image with the other constructs of the model are also confirmed. Destination image is an antecedent of value (Kim et al., 2013), satisfaction (Prayag & Ryan, 2012), and of behavioral intentions (Bigné et al., 2009), confirming that it exercises a much more significant influence than country image on the model as a whole.
It is also confirmed that value is an antecedent of satisfaction (Chen & Chen, 2010), but the direct influence of value on behavioral intentions is not confirmed, and this study therefore agrees with the results of Chen and Tsai's (2007) and Sun et al.'s (2013) findings, who did not find this relationship significant, the former in a study performed in Kengtin, a coastal destination in southern Taiwan, the latter in a study carried out in Haikou and Sanya City, two of the most popular coastal tourism destinations in Hainan Island in China. Thus it seems to be confirmed that this relationship is not significant in sun-and-sand tourist destinations.
The structural path between satisfaction and behavioral intentions is consistent with tourist destination literature, confirming the direct and positive relationship (Chen & Chen, 2010;Chen & Tsai, 2007;Forgas-Coll et al., 2012;Prayag & Ryan, 2012). The greater the tourists' satisfaction, the more it influences their behavioral intentions, and satisfaction is therefore decisive in word-of-mouth, recommendations, and revisit intentions for the tourist destination.
The analysis performed of the two tourist destinations shows differences in some of the relationships. In the relationship between country image and destination image, we observe that the influence of country image (people character) on the destination image is significantly stronger in Lloret de Mar than in Cancun. This difference could be related to the typology of the tourist destination. Tourists relate much more to the population as a whole in a secondgeneration destination because tourist services are spread throughout the destination. On the other hand, in a third-generation destination tourists relate mostly to the service personnel of the resort and have less contact with the local population (Russo & Segre, 2009). We also observed that the influence of country image (country character) on destination image is significant in Cancun, but not in Lloret de Mar. This would imply that country character is more important for tourists visiting developing countries than for those visiting developed countries (Campo & Álvarez, 2010). One possible explanation could be that tourists visiting Lloret de Mar are not affected by country character in the perception of the destination image because it is a destination in a member country of the European Union, and it is assumed not to have deficiencies regarding democracy, development, or international visibility. On the other hand, Mexico is a developing country, and Cancun is located in a region in which one can easily perceive the socio-economic imbalances in the population (Torres & Momsen, 2005). Also, Mexico is exposed to the negative impact on public opinion of high indices of corruption perception, and of bribe payers (Transparency International, 2014), so any change or improvement in international indicators affecting country character would have a positive influence on the perception of the destination image. On the other hand, results suggest that a direct relationship between country image and destination image only exists in Cancun, the halo effect would therefore appear to be stronger at this tourist destination. According to the relationship between destination image and value, the results show that the relationship is stronger in Lloret de Mar than in Cancun. This difference indicates that for tourists in second-generation resorts, infrastructure, services, reputation, and access have a greater impact on monetary and non-monetary costs than in third-generation resorts. On the other hand, for third-generation destinations, as is the case in Cancun, tourists have their tourist experience in enclosed hotel complexes far from the urban center, therefore the influence of the destination image on value probably decreases because the infrastructure is located in the tourist destination area, not directly within the city as is the case in Lloret de Mar.
The direct relationship between destination image and behavioral intentions is significant in Lloret de Mar, but not in Cancun. This low value in Cancun seems to confirm that the relationship between destination image and behavioral intentions has an indirect effect through value and satisfaction, and not a direct one.
The results in the relationships between value and satisfaction and between satisfaction and behavioral intentions are very similar and do not allow further interpretations. The differences are only significant regarding the R 2 value, because R 2 of perceived value in Lloret de Mar are higher than Cancun (54% for Lloret de Mar and 37% for Cancun) and, also, in satisfaction (84% for Lloret de Mar and 69% for Cancun), which indicates that value and satisfaction will be explained by some variable not included in this study.
Also, the results indicate numerous implications for the tourism promotion agencies of both destinations. As the results show, destination image is the key variable since it is essential for the tourist to value the destination, be satisfied with it, recommend it, talk positively about it, and intend to visit it again. This means that tourism policy managers of the two destinations must work to continue to improve the hotel structure, tourist services, and access, and prevent mass tourism at these destinations from having negative repercussions on the reputation of the destinations. Furthermore, each of the destinations has to continue to offer its own concept of "exoticism". Lloret de Mar must continue to exploit the concept of a European and Mediterranean destination, situated in a country with an ancient civilization, which is opening up to new tourist segments, and prevent the continued association of the destination's exoticism with sex, street parties, cheap alcohol, exotic food, and few restrictions. Cancun has to continue to reinforce the "exoticism" derived from the concept of a Caribbean destination, but also to "sell" the secondary tourist attractions of its surroundings, such as the numerous archeological sites of the Mayan civilization. However, in order to continue to increase this influence tourism policy managers must continue to work on the improvement of the cognitive elements of the destination that are within their sphere of competence and/or influence, especially in the case of Cancun. Any change in this direction will be decisive for satisfaction of tourists. Tourists need to find adequate the investment in time, effort, and money to travel to the destination. Only then, tourists are able to recommend and be willing to return to the destination.
With respect to public policies, and especially in the case of the Mexican destination, any reform or action to improve the perception of the Mexican democratic system, greater technological development, or playing a positive part in international politics, rather than being associated with corruption, violence, or drug cartels, will directly and positively influence Cancun's destination image. Also, greater redistribution of tourism services throughout the destination so that tourists have more contact with the local population, would also improve the influence of people character on the destination image of Cancun instead of continuing to develop closed hotel resorts removed from the local population.
One of the limitations of this study is that it considers only two tourist destinations, so care must be taken when extrapolating the results to other destinations. Furthermore, the use of convenience sampling could decrease external validity. Future investigations could consider testing the model in more tourist destinations, maintaining the comparative analysis between second-and third-generation destinations, as well as aiming for a better representation of the tourist population in the sample.