How does confirmation of motivations influence on the pre- and post-visit change of image of a destination?

Asunción Beerli-Palacio (Universidad de Las Palmas de Gran Canaria, Las Palmas, Spain)
Josefa D. Martín-Santana (Universidad de Las Palmas de Gran Canaria, Las Palmas, Spain)

European Journal of Management and Business Economics

ISSN: 2444-8494

Article publication date: 17 July 2017

Abstract

Purpose

The purpose of this paper is to analyse the influence of the confirmation of the motivations of tourists in changing image of a tourist destination pre- and post-visit. That is, considering whether once the tourist has made the trip, depending on whether their expectations have been met and confirmed motivations, will have a more or less image gap.

Design/methodology/approach

The authors conducted an empirical study with a representative sample of leisure tourists to Tenerife (Canary Islands, Spain) of both sexes, 16 or more years of age, and visiting the island of Tenerife for the first time from abroad and from the rest of Spain. The final sample was 411 participants.

Findings

The results verify that the confirmation of the intellectual and escape motivations influences directly and positively change cognitive image pre- and post-visit. The fact that the affiliation motivations do not influence the cognitive image gap may be due to that tourists who visit a destination stay with friends or family and for this they interact less with the destination, which will imply that the cognitive image pre- and post-visit do not vary.

Originality/value

This research has sought to contribute towards a better understanding of the area, which is concerned, with the image of destinations and, more specifically, the concept of how the image changes after a visit to the destination. In this sense, and given the of lack empirical evidence about how confirmation of motivations influences on destination image gap, this research aims to contribute to the improvement of knowledge about the personal factors that influence the change of the pre- and post-visit destination image.

Keywords

Citation

Beerli-Palacio, A. and Martín-Santana, J.D. (2017), "How does confirmation of motivations influence on the pre- and post-visit change of image of a destination?", European Journal of Management and Business Economics, Vol. 26 No. 2, pp. 238-251. https://doi.org/10.1108/EJMBE-07-2017-014

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Asunción Beerli-Palacio and Josefa D. Martín-Santana

License

Published in the European Journal of Management and Business Economics. Published by Emerald Publishing Limited. This article is published under the Creative Commons Attribution (CC BY 4.0) licence. Anyone may reproduce, distribute, translate and create derivative works of this article (for both commercial and non-commercial purposes), subject to full attribution to the original publication and authors. The full terms of this licence may be seen at http://creativecommons.org/licences/by/4.0/legalcode


Introduction

From an academic point of view, tourism has aroused great interest and has been the subject of a great deal of research that has contributed to a greater knowledge of the mechanisms that regulate supply and demand in tourism. The marketing literature highlights the importance of the image of tourist destinations as an object of study, as it represents one of the key factors affecting the consumer in all phases of consumption of the tourism product (Kim et al., 2009; Yilmaz et al., 2009; Nicoletta and Servidio, 2012). In this sense, Giraldi and Cesareo (2014) demonstrate the existence of significant differences in the dimensions of the cognitive image and in the affective image of a destination among the tourists who visit a destination for the first time, as well as repeat visitors (repeaters).

The importance of the image as an element that influences the behaviour of the tourist has been treated in the literature, basically, with respect to the “choosing a holiday” phase (Pike and Ryan, 2004; Hyde, 2008). Only recently have studies emerged that have attempted to deepen the understanding of the influence of the perceived image of destinations on consumer behaviour during the different phases of the travel process (before, during, and after). In this sense, some authors agree that there is a scarcity of studies on the evolution of the image during the different phases of the trip: before, during, and after the visit (Kim et al., 2009; Yilmaz et al., 2009), in spite of the importance for tour operators of knowing the differences between the image held prior to the trip and that which is held subsequently. It would also be effective in determining which factors can influence the differences between the pre- and post-image of a destination in order to be able to act on them and make them the focus of interventions. In short, although there is a multiplicity of works on the image of tourist destinations and numerous studies have defined a theoretical framework, there is still a lack of research that empirically verifies the factors that can influence the gap in the image that occurs before and after the visit (Young, 1999; Tasci and Gartner, 2007). Although the study by Tasci and Gartner (2007) has made it possible to construct a model of the complex relationships connected to the evolution of the image of a tourist destination, many of them still have to be empirically contrasted. For these authors, it is important to study the antecedents of image formation, taking into account the possibility that there is a gap between the pre-visit and post-visit image, resulting in all the factors that have influenced the confirmation of both constructs.

From a conceptual point of view, there is general agreement (Baloglu and Brinberg, 1997; Walmsley and Young, 1998; Baloglu and McCleary, 1999a, b; Baloglu and Mangaloglu, 2001; Chen and Uysal, 2002; Beerli and Martín, 2004a, b; Pike and Ryan, 2004; Hosany et al., 2006; Pike, 2009) in considering the image as the result of three components that are closely interrelated: perceptual/cognitive, which relates to the beliefs of individuals about the attributes that characterise a tourist destination; affective, which refers to the emotional response or feelings that individuals express about a place; and, global, which corresponds to the overall impression, positive or negative, of the place. In addition, the cognitive component is an antecedent of the affective, since the emotions are also influenced by rational elements, and the cognitive component directly influences the global image of a destination, as well as indirectly through the contribution of the affective component (Holbrook, 1978; Russel and Pratt, 1980; Anand et al., 1988; Stern and Krakover, 1993; Beerli and Martín, 2004a, b).

The image of a destination evolves from a focus on the place and its cognitive components to an approach based on the experience of the destination, to arrive, in the end, at a complex image formed after the visit (Mackay and Mcvetty, 2002; Lee, Kang, Reisinger and Kim, 2012). As Lee, Kang, Reisinger and Kim (2012) affirm, 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 image after the trip is less favourable than the image before travel. The incongruity between the pre- and post-visit image influences the tourist experience, satisfaction, and post-trip behaviour. For these authors, it is necessary to delve into the intrinsic factors that cause the change that occurs between pre- and post-visit image. In fact, variables such as the motivations that the tourist has before visiting a destination and the confirmation of those motivations after the visit can influence the change of image before and after the visit to the destination. The lack of empirical work that analyses how the confirmation of the motivations of tourists influences the gap in the image of a destination pre- and post-visit has led us to propose the present investigation, which aims to analyse the degree to which the confirmation of motivations, once the trip is realised, can influence how the image has changed after the visit. To this end, we aim to contribute to a better understanding of the factors intrinsic to the tourist that influence the change in the image of a tourist destination.

Revision of literature

In general, people travel to particular destinations because these destinations satisfy a series of desires, such as escape from the daily routine, relaxation, and the opportunity to spend quality time with family or friends. These decisions, in turn, are stimulated and reinforced by the attributes of the chosen destination, such as beaches, cultural attractions, shopping facilities, and other attractions (Lee, Guillet, Law and Leung, 2012). From this perspective, these same authors point out that different motivations are associated with different destinations, demonstrating the link between motivations and the image of a destination. In this context, numerous studies have shown that motivations are personal factors that influence the potential tourist’s perception of image during the pre-visit phase – that is, during the process of choosing a tourist destination (Beerli and Martín, 2004a, b; Gursoy and McCleary, 2004; Hyde, 2008).

Motivation – understood as a state of necessity that pushes the individual to act in a certain way that is assumed will lead to a desirable sense of satisfaction – is a key personal factor in reducing travel alternatives and in choosing a potentially rewarding destination. It is, therefore, an internal mechanism that leads individuals to act in a concrete way in order to satisfy their desires and needs (Nicoletta and Servidio, 2012), which is to say, their reason for taking the trip. According to Yoon and Uysal (2005), motivation plays a determining role in many phases of the behavioural process of the tourist, since it is an element that drives the search for new information (Pike and Ryan, 2004), a filter for the projected image and the criterion for the choice of destination (Um and Crompton, 1990), and an element of differentiation among tourists visiting the destination for the first time, as well as repeaters, with particular reference to familiarity as opposed to novelty (Hu and Ritchie, 1993; Kaplanidou, 2007).

The main role attributed to motivation is that it is a personal factor that influences the formation of the image before and during the visit (Beerli and Martín, 2004a). However, there are different theories for understanding motivations, such as Maslow’s hierarchy of needs, Plog’s allocentric-psychocentric typology, expectation-value theories, and the push-pull paradigm, the latter being the one that enjoys greater acceptance in the literature – although it is often criticised for being an excessively orthodox approach to understanding motivations (Chen and Chen, 2015; Prayag and Hosany, 2014). According to Goossens (2000), motivations are related to the needs or objectives of individuals (“push” factors). In addition, there are marketing stimuli (“pull” factors) that allow the consumer to gain knowledge relating to the attributes that characterise the tourist destination and can modify the reason for taking the trip, or provide new motivations. In particular, push factors are internally generated drivers that instil in the tourist the need to look for signs in objects, situations, or events in order to reduce uncertainty; while pull factors are generated externally and help to gain a better understanding of the attributes of a destination, reinforcing motivations or “push” factors (Gnoth, 1997). In this context, and by way of summary, Lee, Guillet, Law and Leung (2012) point out that pull factors are related to external and cognitive aspects of a destination (beaches, cultural attractions, etc.), while push factors are related to the internal and emotional aspects of the trip (rest, relaxation, adventure, etc.). In this sense, push factors are those that propel an individual to travel to a destination in order to meet his or her own needs, and pull factors – or extrinsic motivations – are those attributes of a destination that push individuals towards choosing of a particular place (Seebaluck et al., 2015).

According to Chon (1989), pull factors represent the elements of attraction of a place and can be classified into three categories: static factors, i.e., natural environment, climate, and historical/cultural attractions; dynamic factors, including hotels, services, sport, leisure activities, and political conditions, and current decision-making factors, i.e., marketing, prices in the country or region of origin in comparison with prices at the destination, etc.

The model proposed by Lubbe (1998) shows how the “push” and “pull” factors act in concert to generate the individual’s motivation to travel, transforming him or her into a potential tourist. The moment the potential tourist selects a destination as a possible choice for a holiday, they have already constructed the initial image of the destination in their mind. In addition, the author distinguishes three orders of preference that the potential tourist can attribute to push and pull factors and which give rise to three categories of tourists: potential tourists who act more in consideration of their needs (“push” factors), potential tourists who have needs that can be satisfied only by specific destinations and, therefore, give more importance to pull factors, and potential tourists who can be impelled equally by “push” and “pull” factors (e.g. potential tourists who have their annual departure plan during which they would consider travelling to any destination). According to Lubbe (1998), the motivation during the pre-visit phase encourages the potential tourist to make a choice and to realise the trip based on the image they have prior to travel.

Wang et al. (2016) indicate that most theoretical and empirical studies suggest that motivations are a precursor to the image of a destination. However, most of them have shown that motivation influences only the affective component of the image (Dann, 1996; Baloglu, 1997; Beerli and Martín, 2004a, b; San Martin and Rodríguez Del Bosque, 2008). However, other studies have shown that there is also a direct relationship between the motivation and the cognitive component of the image (Hernández-Lobato et al., 2006; Li et al., 2010; Wang et al., 2016). Even works such as Sancho and Álvarez (2010) conclude that socio-psychological motivations (physical, cultural, interpersonal, social, and prestige, and resulting from experiences prior to arrival at the destination) directly influence the cognitive component of image, but not the affective component.

In a study by Li et al. (2010), the relationship between motivation, the image of a tourist destination, and post-travel behaviour was analysed. These authors classify motivations into three categories: “intellectual”, connected, for example, with the desire to know the history of the country, to experience different cultures and lifestyles at the destination, to discover the natural environment, to increase knowledge of a place, people, things, etc.; “affiliation”, connected with the desire to visit friends and relatives, spending time with the family away from home, doing things with the whole family, qualitatively improving the time they spend with their children, etc.; and “escape”, connected with the desire to get away from the daily routines of life, to experience adventures, exciting circumstances and fun situations, and to relax and to have time to recuperate from work and daily life. According to these authors, there is no direct relationship between motivations and intention to revisit a place, since this relationship is influenced by the image of the tourist destination. The authors show that the different motivations that drive travel have a direct effect on the image of the tourist destination and an indirect one on the intention to repeat a visit. This is because if the image of the destination during the trip does not satisfy the motivations that have induced the tourist to travel, it generates a global dissatisfaction that results in failure to return to the destination in the future (Li et al., 2010). In other words, the authors empirically demonstrate that “intellectual” and “affiliation” motivations have a positive influence on the cognitive dimension of the image; while only the “escape” motivation has a positive impact on the affective component of the image.

Under this framework, the present work aims to evaluate whether these motivations have effects on the gap formation between the pre- and post-visit image. In this sense, we seek to assess if once the tourist has made the trip, depending on whether his expectations have been met and his motivations confirmed, they will have a post-visit image which is more or less distant from the pre-visit image, with a consequent generation of a greater or lesser gap. Moreover, since the theory shows that there is no agreement in the literature about which components of the image are influenced by motivations, our analysis can contribute towards clarifying this debate.

In summary, and with the ultimate aim of evaluating the effects of the confirmation of motivations on the gap between the components of the pre- and post-visit image, we propose the following hypotheses:

H1a.

Confirmation of the motivations of tourists affects the gap between the cognitive image, pre- and post-visit.

H1b.

Confirmation of the motivations of tourists affects the gap between the affective image, pre- and post-visit.

H1c.

Confirmation of the motivations of tourists affects the gap between the global image, pre- and post-visit.

Additionally, and according to the doctrinal revision, the model also gathers the interrelations between the cognitive, affective, and global image, in a way that shows that the cognitive image directly influences the affective and global image, and indirectly the global image, through the affective image, which also directly influences the global image (see Figure 1).

Methodology

The study population in the present research focusses on leisure tourists in Tenerife, the unit of analysis being tourists of both sexes, 16 years and older, who are visiting the island for the first time from abroad or from the elsewhere in Spain.

The sample size amounted to 411 tourists, the assumed error being, therefore, ±4.93 per cent for a 95% confidence interval. For the selection of the sample, a method of empirical selection was followed by the quotas related to the nationality, sex, and age dimensions, with affixation proportional to the number of tourists in each of the established dimensions. The field work was carried out during the months of June and July 2015 at the most popular tourist attractions in Tenerife frequented by travellers: Las Américas, Los Cristianos, Costa Adeje, El Médano, Candelaria, Puerto de la Cruz, Garachico, and Los Gigantes. The profile of the respondents was similar to that of the population. There are almost as many women (54 per cent) as men (46 per cent). Most respondents ranged from 25 to 44 years (45.40 per cent) or between 45 and 64 years (30.50 per cent), followed by those 24 years and younger (11.20 per cent) and 65 and over (12.90 per cent). With regard to the country of origin, the majority come from the UK (37.37 per cent), Germany (14.41 per cent), Spain (12.60 per cent), Nordic countries (10.34 per cent), the Netherlands (7.06 per cent), and others (18.22 per cent).

In relation to the measurement scales, a Likert scale of eight items and seven points was used to measure the motivations of the tourists based on the scale proposed by Li et al. (2010). With this scale, we assessed the degree of confirmation for each motivation once the trip was realised. In order to measure the cognitive, affective, and global image gap, the works of Beerli and Martín (2004a, b) were referenced, using a Likert scale of seven points and ten items to measure the cognitive image, two items to measure the affective image, and one item to measure the global image. The items on the scale of the cognitive image are listed in Table I. The two items on the scale of the affective image are “pleasant place” and “fun place”. This affective image scale obtained a reliability, measured through Cronbach’s α, of 0.7. To assess the gap, the respondent assessed the degree to which each item in the cognitive, affective, and global image had been better, equal to, or worse than expected, according to the information that was obtained before the trip on a scale ranging from −3 to +3, where −3 is much worse than expected, 0 is equal to expected, and +3 is much better than expected.

Results

Validation of measurement scales

As a prior step to the validation of the scale that determines the gap of the pre- and post-visit image, a frequency of the items that conformed to this scale was made in order to analyse its distribution. All items were rated on a scale of −3 to +3, where −3 is much worse than expected, 0 is equal to expected, and +3 much better than expected. The results reflect that the percentage of negative gap (−3 to −1) is very small in relation to all the attributes of the destination (less than 5 per cent), as well as in the items of the affective image gap scale and the gap of the global image. Due to this, and for all items, the values of −3, −2, −1 and 0 were recoded into a single category, which has been labelled “Same as expected or slightly worse”. In this way, the items of the cognitive, affective, and global image gap are taken as possible values 0, +1, +2 and +3.

The final results of the second-order confirmatory factor analysis applied to the recoded scale of four states of the cognitive image gap of the destination determined three dimensions, which have been labelled as “Natural and Artificial Resources” (RESNATART), “Tourism Activities” (ACTIVTOUR) and “Environment” (ENVIRONMENT). 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) demonstrate the suitability of a multidimensional model (χ2(32)=140.75, p=0.000, CFI=0.92, RMSEA=0.09), since it presents higher levels of significance and adjustment 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 finally been formed by three dimensions and by the items shown in Table I. The items removed from the original scale showed low standardised estimators and their significance was gleaned from other items of the scale.

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 adjustment indicators. In this respect, the results obtained show that other indicators of 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). For this reason, we can conclude that the specified model accurately reproduces the observed covariance matrix. This measurement model shows an adequate fit, since the CFI value is higher than 0.90, although the RMSEA value is at 0.09 (Mathieu and Taylor, 2006). Following Anderson and Gerbing (1988), and as shown in Table II, the model shows acceptable individual reliability, since the relationship between each item and its respective dimension is statistically significant with higher than, or very close to, standardised regression weights in their majority at 0.7, and with values of the statistic t also significant. As for the measures of internal consistency, the values of the composite reliability (CR) of the gap dimensions of the cognitive image reach values higher than, or close to, 0.70, and those of the extracted variance (AVE) higher than, or close to, 0.50. Cronbach’s α values corroborate those obtained in CR (see Table II). It can be affirmed, therefore, that the scale of the cognitive image gap is a construct of a multidimensional nature formed by three dimensions, which show discriminant validity, since the AVE of each one of the dimensions is superior to the square of its correlation with the remaining dimensions. These results indicate that the measurement model can be considered valid, although it would be advisable to replicate it in other contexts and even to extend or modify the content of some of the dimensions in order to raise its level of reliability.

With respect to the confirmation scale of the motivations, the final results of the confirmatory factor analysis show the existence of the three types of motivations proposed by Li et al. (2010), which have been labelled as “Intellectual or knowledge motivations” (INTMOT), “Escape motivations” (ESCMOT), and “Affiliation or social motivations” (AFILMOT). However, to analyse the dimensionality of this scale, we also estimated a new model in which all items are linked to a single factor. The results of this new model (χ2(20)=467.85, p=0.000, CFI=0.65, RMSEA=0.23) demonstrate the suitability of a multidimensional model (χ2(17)=69.48, p=0.000, CFI=0.96, RMSEA=0.08), as it presents higher levels of significance and better adjustment indexes. In fact, the analysis of χ2 differences reveals the existence of significant differences (Dif. χ2=398.37, Dif. g.d.l.=3, p=0.000). Therefore, this confirmation scale of travel motivations has finally been formed by the dimensions and items shown in Table III. The items removed from the original scale showed low standardised estimators and their significance was gleaned from other items of the scale.

Although the results of this measurement model indicate that it is statistically significant (χ2(17)=69.48, p=0.000), as we have already noted, this statistic depends on the size of the sample analysed, hence the need to analyse other adjustment indicators. In this respect, the results show that other indicators of global fit of the model are among the values recommended by the literature (CFI=0.96, NFI=0.95, TLI=0.93, RMSEA=0.08). Therefore, we can conclude that the model correctly reproduces the observed covariance matrix. This measurement model shows a very satisfactory adjustment since the value of CFI is higher than 0.95 and the value of RMSEA does not exceed the recommended maximum of 0.08 (Mathieu and Taylor, 2006). Following Anderson and Gerbing (1988), and as shown in Table IV, the model shows an acceptable individual reliability, since the relationship between each item and its respective dimension is statistically significant, presenting statistically significant t values, albeit with standardised regression weights which are not quite satisfactory, with two of them not exceeding the value of 0.7. As for the internal consistency measures of each of the motivation typologies, the values of the CR indicator reach values higher than, or very close to, 0.70, although one of the variances extracted (AVE) does not exceed 0.50 – though it is very close (0.445). The values of Cronbach’s α corroborate those obtained in the CR. In addition, the three dimensions of the scale of motivations show discriminant validity, since the AVE of each of the dimensions is superior to the square of its correlation with the other dimensions. Therefore, these results indicate that the measurement model can be considered as valid, although, as in the previous case, it would be advisable to replicate it in other contexts and even extend or modify the content of some of the dimensions in order to raise its level of reliability.

Influence of the confirmation of the motivations on the gap in the pre- and post-visit image of the destination

Before proceeding to the contrast of the hypotheses, a new variable has been created for each one of the dimensions of the cognitive and affective image gap, as well as for the motivations, 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 AFC. These variables have been labelled with the same name given to the dimensions. On the other hand, to contrast H1a-H1c, a model of structural equations for each of the three typologies of motivations (intellectual, escape, and affiliation) has been made, since the empirical evidence in this respect establishes conclusions in function of the type of motivation and, in addition, the sample size is not high enough to fit a single model. Moreover, if one wanted to adjust a single model, one would have to opt for a model path with the consequent loss of information that would entail.

Figure 1 shows the adjustments of the three models, which can be considered as acceptable. From the results obtained, it is clear, first, that the confirmation of the “intellectual” and “escape” motivations directly and positively influence the cognitive image gap, unlike with the confirmation of the “affiliation” motivation; second, that the affective image gap is not influenced by the confirmation of motivations in any of the three typologies; and, third, that the gap in the global image is directly and negatively influenced only by the confirmation of the “escape” motivation to a level of significance of 1.7 per cent. The lack of a statistically significant relationship between the confirmation of motivations relating to the affective image gap in two cases and the global one in all three cases may be due to the fact that the cognitive image gap has a strong influence on the affective image gap, and the latter on the global image gap, generating only indirect confirmation of motivations effects on the gap in the affective and global image. In the literature, there is some controversy in this regard, since there are studies in which the relationship between motivations and affective image is not confirmed (Sancho and Álvarez, 2010; Wang et al., 2016) Most studies have not contrasted the relationship between motivations and the global image. Therefore, these results allow us to accept H1a, and partially H1c, but lead us to reject H1b. On the other hand, it is worth noting that having adjusted the model for each of the different types of motivation implies a greater robustness to the results, since it is possible to analyse the stability, or otherwise, of the results (Figure 2).

Discussion, conclusions, and implications

In the empirical analysis developed in line with the theoretical model, we have attempted to analyse the effects on the image gap of factors closely connected to the personal sphere of the individuals, and that refer to the confirmation of the possible motivations for travel to the destination. The added value of this work in these aspects is, on the one hand, in the consideration of the confirmation of motivations as an antecedent and not in the motivations themselves, as is usual in the empirical work collected in literature; and, on the other hand, the consideration in this relationship of the pre- and post-visit change of image in its three components.

The results indicate that with the confirmation of the three types of motivation (intellectual, escape, and affiliation) analysed individually, only the first two types influence directly and positively the cognitive image gap. This result is in line with the revised literature, establishing that the tourists who satisfy their reason for the trip during the visit will have an image of the destination after the experience that is better than the one they had initially, generating a positive cognitive image gap. The fact that the “affiliation” motivation does not influence the cognitive image could be due to the fact that tourists who visit a destination to visit friends or to be with the family interact less with the destination, which means that the pre- and post-visit cognitive image may not vary. We do not reach the same conclusion if we consider the effect of the confirmation of motivations on the gap in the affective and global image, since there is no significant relationship between the confirmation of motivations and the gap of these components of the image, with the exception of the confirmation of the “escape” motivation, which does present a statistically significant relationship with the global image gap. Nevertheless, there is an indirect influence of the confirmation of the different motivations on the gap in the affective and global image through the gap in the cognitive image; and the fact that the relationship between the gap in the cognitive and affective image is so strong as to justify the one that absorbs the indirect effects and cancels the direct ones. With regard to the direct and negative effect of the confirmation of the “escape” motivation on the gap in the global image, this could be consequence of the destination chosen to be the object of analysis not being characterised as being an “adventure” destination, although some leisure activities related to adventure can be found; this has repercussions on that the global image post-visit, which does not improve with respect to the image that was had before the visit to the destination took place – although a perceptible improvement in the cognitive image does occur. On the other hand, the fact that the cognitive image gap does not directly influence the global image gap, as one might expect, may be a consequence of the indirect effect which occurs through the affective image gap, since the relationship between the cognitive image gap and the affective image gap is so strong that it cancels the direct effect between the cognitive and global image gap.

This research has sought to contribute to a greater knowledge in the field of tourist destination image and, more specifically, about the concept of image change after a destination is visited, as a consequence of the confirmation of the motivations of tourists.

From an academic point of view, an attempt has been made to continue advancing the development of the topic in order to better understand how the confirmation of the different motivations of the tourists influences the gap in the pre- and post-visit image. More specifically, and based on a conceptual structure of image with theoretical support, it has been verified that the image of the tourist destination can be subject to change before and after the visit in function of the confirmation of the motivations of the tourists. Additionally, we have analysed the psychometric properties of the scales used, the analysis of which could prove useful for subsequent studies.

From a practical point of view, a better understanding of the motivations of tourists which influence the pre- and post-visit change in image will help operators from the sector and the public institutions responsible for the commercial management of the destinations to project an image that is as close to reality as possible and to meet the various needs of tourists. Based on the results of the present investigation, it is essential that destinations satisfy the “intellectual” and “escape” motivations of tourists so that the image they take back is better than expected. Therefore, the promotion of destinations must be based on a positioning that attracts tourists whose motivations are in line with what the destination offers. Conversely, when tourists travel to a destination on the grounds of “affiliation”, there is no positive change in the destination’s image before and after a visit to it. This may be a consequence of tourists spending more time with friends and family and less time interacting with the destination through visiting places of interest.

Although we have attempted to carry out the research following criteria of scientific rigour with the objective of providing empirical evidence that contributes to a greater knowledge and understanding of the process which forms the image gap in tourist destinations, we are aware of its limitations, both conceptual and methodological. From a conceptual point of view, the research is limited to the context of its own objectives and we are aware that there are other personal factors that can also affect the process of image change, such as the psychographic profile of tourists, which is not included in our research (personality, values, lifestyles, etc.). In addition, it would be interesting to extend the analysis to repeat tourists in order to discover the effect of prior knowledge and familiarity with a place on the image gap. Similarly, the role that culture plays on the formation of the gap could be the subject of further work. From a methodological perspective, this work, like any other empirical research, presents limitations that affect the evaluation and generalisation of its results. In structural models, causality must be understood in terms of statistical association and not under the conditions of an experimental design. However, we have tried to propose causal relations supported theoretically on the basis of the theoretical foundations raised in the section of literature review. Finally, the generalisation of the results constitute another limitation, since the scope of the investigation only generalises the results of the analysis to the population on which the sample is based and the tourist destination of Tenerife. It would, therefore, be advisable to replicate this research in other contexts and to analyse the factors that influence the perceived image in other tourist destinations.

Figures

Influence model of the confirmation of motivations in the image gap

Figure 1

Influence model of the confirmation of motivations in the image gap

Results of the influence model of the confirmation of the motivations in the image gap

Figure 2

Results of the influence model of the confirmation of the motivations in the image gap

Definite items of the destination attribute scale

Dimensions Item code Items
Natural and artificial resources COG1 Climate
COG2 Natural resources (countryside, national parks, flora and fauna, etc.)
COG3 Tourism infrastructure (accommodation, restaurants, shopping centres, golf courses, etc.)
COG4 General infrastructure (highways, airports, public transport, sanitation, internet, etc.)
Tourism activities COG5 Leisure activities and recreation (theme parks, tourist activities, golf, wellness centres, etc.)
COG6 Nightlife (bars, night clubs, casinos, etc.)
COG7 Adventure sports (paragliding, rafting, etc.)
COG8 Sporting activities (sailing, windsurfing, cycling, etc.)
Environment COG9 Environment (cleanliness, clean air, etc.)
COG10 Security

Confirmatory factorial analysis of the cognitive image gap scale

Relaciones causales Estimadores estandarizados t p Consistencia interna
RESNATART←GAPCOGIMAG 0.958 FC=0.818
AVE=0.607
α=0.699
ACTIVTOUR←GAPCOGIMAG 0.614 5.704 0.000
ENVIRONMENT←GAPCOGIMAG 0.726 6.009 0.000
COG1←RESNATART 0.536 FC=0.726
AVE=0.401
α=0.723
COG2←RESNATART 0.672 8.877 0.000
COG3←RESNATART 0.660 8.803 0.000
COG4←RESNATART 0.655 8.769 0.000
COG5←ACTIVTOUR 0.604 9.712 0.000 FC=0.811
AVE=0.523
α=0.802
COG6←ACTIVTOUR 0.591
COG7←ACTIVTOUR 0.824 11.774 0.000
COG8←ACTIVTOUR 0.837 11.832 0.000
COG9←ENVIRONMENT 0.728 FC=0.643
AVE=0.475
α=0.641
COG10←ENVIRONMENT 0.648 8.257 0.000

Definitive items of the trip motivation confirmation scale

Dimensions Item code Items
Intellectual or knowledge motivations MOT1 Get to know different cultures and lifestyles
MOT2 Increase knowledge of other places, people, or things
Escape motivations MOT3 Escape from the daily routine
MOT4 Seek adventure and participate in exciting activities
MOT5 Fun and entertainment
Affiliation or social motivations MOT6 Visit friends and relatives
MOT7 Spend time with family away from home
MOT8 See and do new things with the family

Confirmatory factorial analysis of the scale of confirmation of motivations

Causal relationships Standardised estimators t p Internal consistency
MOT1←INTMOT 0.763 FC=0.727
AVE =0.572
α=0.724
MOT2←INTMOT 0.749 8.349 0.000
MOT3←ESCMOT 0.464 FC=0.698
AVE =0.445
α=0.718
MOT4←ESCMOT 0.767 7.624 0.000
MOT5←ESCMOT 0.729 7.670 0.000
MOT6←AFILMOT 0.492 10.489 0.000 FC=0.853
AVE =0.675
α=0.822
MOT7←AFILMOT 0.901 21.574 0.000
MOT8←AFILMOT 0.986

References

Anand, P., Holbrook, M.B. and Stephens, D. (1988), “The formation of affective judgements: the cognitive-affective model versus the independence hypothesis”, Journal of Consumer Research, Vol. 15 No. 3, pp. 386-391.

Anderson, J.C. and Gerbing, D.W. (1988), “Structural equation modeling in practice: a review and recommended two-step approach”, Psychological Bulletin, Vol. 103 No. 3, pp. 411-423.

Baloglu, S. (1997), “The relationship between destination images and sociodemographic and trip characteristics of international travellers”, Journal of Vacation Marketing, Vol. 3 No. 3, pp. 221-233.

Baloglu, S. and Brinberg, D. (1997), “Affective images of tourism destinations”, Journal of Travel Research, Vol. 35 No. 4, pp. 11-15.

Baloglu, S. and Mangaloglu, M. (2001), “Tourism destination images of Turkey, Egypt, Greece, and Italy as perceived by US-based tour operators and travel agents”, Tourism Management, Vol. 22 No. 1, pp. 1-9.

Baloglu, S. and Mccleary, K.W. (1999a), “A model of destination image formation”, Annals of Tourism Research, Vol. 26 No. 4, pp. 868-897.

Baloglu, S. and Mccleary, K.W. (1999b), “US international travellers’ images of four Mediterranean destinations: a comparison of visitors and no visitors”, Journal of Travel Research, Vol. 38 No. 2, pp. 144-152.

Beerli, A. and Martín, J.D. (2004a), “Factor influencing destination image”, Annals of Tourism Research, Vol. 31 No. 3, pp. 657-681.

Beerli, A. and Martín, J.D. (2004b), “Tourists’ characteristics and the perceived image of tourist destinations: a quantitative analysis – a case study of Lanzarote, Spain”, Tourism Management, Vol. 25 No. 5, pp. 623-636.

Chen, J.S. and Uysal, M. (2002), “Market positioning analysis: a hybrid approach”, Annals of Tourism Research, Vol. 29 No. 4, pp. 987-1003.

Chen, L.J. and Chen, W.P. (2015), “Push-pull factors in international birders’ travel”, Tourism Management, Vol. 48, pp. 416-425.

Chon, K. (1989), “Understanding recreational travelers’ motivation, attitude and satisfaction”, The Tourist Review, Vol. 44 No. 1, pp. 3-7.

Dann, G.M.S. (1996), The Language of Tourism: A Sociolinguistic Perspective, CAB International, New York, NY.

Giraldi, A. and Cesareo, L. (2014), “Destination image differences between first-time and return visitors: an exploratory study on the city of Rome”, Tourism and Hospitality Research, Vol. 44 No. 4, pp. 197-205.

Gnoth, J. (1997), “Tourism motivation and expectation formation”, Annals of Tourism Research, Vol. 24 No. 2, pp. 283-304.

Goossens, C. (2000), “Tourism information and pleasure motivation”, Annals of Tourism Research, Vol. 27 No. 2, pp. 301-321.

Gursoy, D. and McCleary, K.W. (2004), “An integrative model of tourists’ information search behavior”, Annals of Tourism Research, Vol. 31 No. 2, pp. 353-373.

Hernández-Lobato, L., Solis-Radilla, M.M., Moliner-Tena, M.A. and Sanchez-Garcia, J. (2006), “Tourism destination image, satisfaction and loyalty: a study in Ixtapa-Zihuatanejo, Mexico”, Tourism Geographies, Vol. 8 No. 4, pp. 343-358.

Holbrook, M.B. (1978), “Beyond attitude structure: toward the informational determinants of attitude”, Journal of Marketing Research, Vol. 15 No. 4, pp. 545-556.

Hosany, S., Ekinci, Y. and Uysal, M. (2006), “Destination image and destination personality: an application of branding theories to tourism places”, Journal of Business Research, Vol. 59 No. 5, pp. 638-642.

Hu, Y. and Ritchie, J.R.B. (1993), “Measuring destination attractiveness: a contextual approach”, Journal of Travel Research, Vol. 32 No. 2, pp. 25-34.

Hyde, K. (2008), “Information processing and touring planning theory”, Annals of Tourism Research, Vol. 35 No. 3, pp. 712-731.

Kaplanidou, K. (2007), “Affective event and destination image: their influence on Olympic travelers’ behavioral intention”, Event Management, Vol. 10 No. 2, pp. 159-173.

Kim, S., Mckercher, B. and Lee, H. (2009), “Tracking tourism destination image perception”, Annals of Tourism Research, Vol. 36 No. 4, pp. 715-718.

Lee, C., Kang, S., Reisinger, Y. and Kim, N. (2012), “Incongruence in destination image: central Asia region”, Tourism Geographies: An international Journal of Tourism Space, Place and Environment, Vol. 14 No. 4, pp. 599-624.

Lee, H.A., Guillet, B.D., Law, R. and Leung, R. (2012), “Travel motivations and travel distance with temporal advance: a case study of Hong Kong pleasure travelers”, Journal of Destination Marketing & Management, Vol. 1 Nos 1-2, pp. 107-117.

Li, M., Cai, L.A., Lehto, X.Y. and Huang, J.Z. (2010), “A missing link in understanding revisit intention – the role of motivation and image”, Journal of Travel & Tourism Marketing, Vol. 27 No. 4, pp. 335-348.

Lubbe, B. (1998), “Primary image as a dimension of destination image: an empirical assessment”, Journal of Travel and Tourism Marketing, Vol. 7 No. 4, pp. 21-43.

Mackay, K.J. and Mcvetty, D. (2002), “Images of first-time visitors to Queen Charlotte Islands and Gwaii Haanas National Park reserve”, Journal of Park & Recreation Administration, Vol. 20 No. 2, pp. 11-30.

Mathieu, J.E. and Taylor, S.R. (2006), “Clarifying conditions and decision points for mediational type inferences in organizational behavior”, Journal of Organizational Behavior, Vol. 27 No. 8, pp. 1031-1056.

Nicoletta, R. and Servidio, R. (2012), “Tourists’ opinions and their selection of tourism destination images: an affective and motivational evaluation”, Tourism Management Perspectives, Vol. 4, pp. 19-27.

Pike, S. (2009), “Destination brand positions of a competitive set of near-home destinations”, Tourism Management, Vol. 30 No. 6, pp. 857-866.

Pike, S. and Ryan, C. (2004), “Destination positioning analysis through a comparison of cognitive, affective and conative perceptions”, Journal of Travel Research, Vol. 42 No. 4, pp. 333-342.

Prayag, G. and Hosany, S. (2014), “When Middle East meets West: understanding the motives and perceptions of young tourists from United Arab Emirates”, Tourism Management, Vol. 40, pp. 35-45.

Russel, J.A. and Pratt, G. (1980), “A description of affective quality attributed to environment”, Journal of Personality and Social Psychology, Vol. 38 No. 2, pp. 311-322.

Sancho, F. and Álvarez, J. (2010), “Tourism destination image and motivations: the Spanish perspective of Mexico”, Journal of Travel & Tourism Marketing, Vol. 27 No. 4, pp. 349-360.

San Martin, H. and Rodríguez Del Bosque, I.A. (2008), “Exploring the cognitive-affective nature of destination image and the role of psychological factors in its formation”, Tourism Management, Vol. 29 No. 2, pp. 263-277.

Seebaluck, N.V., Munhurrun, P.R., Naidoo, P. and Rughoonauth, P. (2015), “An analysis of the push and pull motives for choosing Mauritius as ‘the’ wedding destination”, Procedia – Social and Behavioral Sciences, Vol. 175, pp. 201-209.

Stern, E. and Krakover, S. (1993), “The formation of a composite urban image”, Geographical Analysis, Vol. 25 No. 2, pp. 130-146.

Tasci, A.D.A. and Gartner, W.C. (2007), “Destination image and its functional relationships”, Journal of Travel Research, Vol. 45 No. 4, pp. 413-425.

Um, S. and Crompton, J.L. (1990), “Attitude determinants in tourism destination choice”, Annals of Tourism Research, Vol. 17 No. 3, pp. 432-448.

Walmsley, D.J. and Young, Y.M. (1998), “Evaluative images and tourism: the use of personal constructs to describe the structure of destination images”, Journal of Travel Research, Vol. 36 No. 3, pp. 65-69.

Wang, C., Qu, H. and Hsu, M.K. (2016), “Toward an integrated model of tourist expectation formation and gender difference”, Tourism Management, Vol. 54, pp. 58-71.

Yilmaz, Y., Yilmaz, Y., Içigen, E.T., Ekin, Y. and Utku, B.D. (2009), “Destination image: a comparative study on pre and post trip image variations”, Journal of Hospitality Marketing & Management, Vol. 18 No. 5, pp. 461-479.

Yoon, Y. and Uysal, M. (2005), “An examination of the effects of motivation and satisfaction on destination loyalty: a structural model”, Tourism Management, Vol. 26 No. 1, pp. 45-56.

Young, M. (1999), “The social construction of tourist places”, Australian Geographer, Vol. 30 No. 3, pp. 373-389.

Corresponding author

Asunción Beerli-Palacio can be contacted at: suny.beerli@ulpgc.es