Tourist attractions as a moderating element in explanatory models for loyalty development

Las atracciones en los destinos turísticos como moderadores en el proceso de lealtad del visitante

Manuel Rey-Moreno^I; Cayetano Medina-Molina^II; Ramón Rufín-Moreno^III

^IUniversidad de Sevilla, Facultad de Ciencias Económicas y Empresariales, Departamento de Administración de Empresas y Comercialización e Investigación de Mercados (Marketing), Avda. Ramón y Cajal, 1, C.P. 41018, Sevilla, España, mrmoreno@us.es
^IICentro Andaluz de Estudios Empresariales, Avda. Leonardo da Vinci, 6, Ed. Ceade I, E-41092, Sevilla, España, cmedina@ceade.es
^IIIUniversidad Nacional de Educación a Distancia, Facultad de Ciencias Económicas y Empresariales, Departamento de Economía de la Empresa y Contabilidad, Paseo Senda del Rey, 11, E-28040, Madrid, España, rrufin@cee.uned.es

ABSTRACT

Many studies have analysed the impact of destination image on tourist satisfaction and loyalty, including different mediating variables, both affective and cognitive. This article will attempt to determine whether the representative model of visitors' future behaviour (satisfaction and loyalty) – viewed in terms of destination image, quality, value, disconfirmation, and emotions – follows a common, universal pattern or whether that behaviour actually differs when the model is applied to destinations offering different attractions.

The paper below analyses disparate emotional behaviour in relation to destinations mentioned in the literature, when value does not play a mediating role between perception of quality and satisfaction with coastal destinations. This study concludes that there is a common pattern for purely urban cultural destinations while a different pattern exists for urban cultural destinations that include beaches among their attractions.

Keywords: Destination type, loyalty, satisfaction, emotions, cultural destinations, seaside.

RESUMEN

Múltiples estudios han analizado el impacto de la imagen de los destinos en la satisfacción y lealtad de los turistas, incluyendo diversas variables mediadoras tanto afectivas como cognitivas. Este artículo intentará determinar si el modelo de comportamiento futuro del visitante (satisfacción y lealtad), analizado en términos de imagen del destino, calidad, valor, disconfirmación y emociones, sigue un modelo común y universal, o si por el contrario difiere entre destinos que ofrecen diferente tipo de atracciones al visitante. 

El trabajo contrasta la existencia de un comportamiento dispar de las emociones en relación con lo expuesto en la literatura, al tiempo que se señala que el valor no juega un rol mediador entre la calidad y la satisfacción para los destinos costeros. Como conclusión se extrae que hay un modelo de comportamiento común entre destinos puramente urbanos, mientras que existe otro diferente para destinos culturales urbanos que cuentan con playa entre sus atractivos turísticos. 

Palabras clave: Tipos de destino, fidelidad, satisfacción, emociones, destinos culturales, lugares costeros.

1.   Introduction

The competition that tourist destinations are currently facing has created a need to understand the process by which these destinations generate satisfaction and loyalty (Agapito, Valle & Mendes, 2011). As a result, the tourism marketing field has made many contributions focusing primarily on what role is played by the image tourists have of a destination.

Many papers have examined the relationships between destination image, tourist satisfaction, and loyalty. In addition to these papers, other studies have highlighted the role of quality, considered both independently (Barroso, Martin & Martin, 2007; Bigné, Sánchez & Sánchez, 2001), and in conjunction with perceived value (Murphy, Pritchard & Smith, 2000; Chen & Chen, 2009; Lam, Shankar, Erramilli & Murthy, 2004), since value can mediate the effect of quality on satisfaction.

However, given that tourist behaviour is influenced to a greater extent by expectations of the destination than by satisfaction per se, it seemed necessary to include the concepts of expectations and disconfirmation in those models (Rodríguez, San Martín & Collado, 2006). Lastly, given the relationship shown between these cognitive variables and affective components, it also seemed advisable to consider emotions in the studies attempting to explain the impact of destination image on tourist satisfaction and loyalty (Bagozzi, Gopinath & Nyer, 1999; Bigné, Andreu & Gnoth, 2005; Rey, Medina & Rufín, 2013; Wirtz & Bateson, 1999).

But despite so many relevant studies, the following question remained unanswered: do the observed relationships continue to appear when they are applied to destinations offering different attractions? This study is an attempt to answer the question of how the explanatory models for the development of tourist satisfaction and loyalty may work differently depending on the attractions available at each destination. More specifically, we will analyse three very different tourist destinations located in two continents. Two of them are "pure" urban cultural destinations, whereas the third, also an urban cultural destination, features a strong seaside component, boasting world-renowned islands and beaches.

Our analysis will attempt to determine whether the representative model – of visitors' future behaviour in terms of destination image, quality, value, disconfirmation, and emotions – follows a common, universal pattern or whether this behaviour actually differs when applied to destinations with different attractions.  

2.   Conceptual framework

2.1 Destination image, satisfaction and loyalty

Several studies verify the relationship between destination image and expectations, given that a destination's image shapes the expectations people have before they travel (Rodríguez et al., 2006). The assumption made in the literature is that expectations have an indirect effect on satisfaction through a process referred to as "expectation disconfirmation".  

Recent studies (Rodríguez & San Martín, 2008) have established that the relationship between expectations and disconfirmation is significant, but positive. Other authors consider that the disconfirmation process is not as relevant as has been assumed until now, whereas what is really important is the effect that expectations have on satisfaction through perceived quality (Spreng & Page, 2001; De Rojas & Camarero, 2008). Lastly, certain studies point out that how expectations directly affect satisfaction is more relevant than the role that expectations may have as a parameter for comparison with the consumer's actual experience (Rodríguez et al., 2006).

The combination of value and quality may have a mediating effect between the consumer's perceptions and their satisfaction; hence, value and quality are critical in developing a tourist destination (Fyall, Callod & Edwards, 2003; Murphy et al., 2000). This relationship has been verified for the tourist sector where value is established as a mediating element between quality and satisfaction, both of which have an effect on loyalty (Murphy et al., 2000; Chen & Chen, 2009; Lam et al., 2004). Meanwhile, Um, Con and Ro (2006) posit that perceived quality has a greater influence on the intention to revisit than satisfaction, while value is merely an antecedent to satisfaction.

Lastly, tourist satisfaction clearly affects loyalty (Alegre & Cladera, 2009; Bigné et al., 2001; Chi & Qu, 2008; Cronin, Brady & Hult, 2000; Hui, Wan & Ho, 2007; Kozak, 2001; Murphy et al., 2000). However, when analysing how satisfaction affects the intention to revisit a destination, one must take into consideration that satisfaction acts as an antecedent to this intention in the short term. However, in the mid- or long term it is not an antecedent where novelty is the variable with greatest impact (Jang & Feng, 2007). Additionally, satisfaction is a necessary but insufficient condition for revisiting a destination (Hong, Lee, Lee & Jang, 2009).

The literature has actually acknowledged the need to study the affective and cognitive components of satisfaction (Dubé, Cervellon & Jingyuan, 2003; Rey, Medina & Rufín, 2013; Wirtz, Mattila & Tan, 2000b; Wirtz, Doreen & Khai, 2000a). Affective variables must be included in studies of service sectors since by nature their consumption is inseparable from consumer experiences (Wirtz et al., 2000a). Affect is a specific mental process that includes emotions, moods, and attitudes. Emotions are high-intensity affective variables related to the eliciting stimuli (Bagozzi et al., 1999); analyzing these emotions enables us to understand consumers' affective state and diagnose their emotional state – and, indirectly, their satisfaction (Dubé & Menon, 2000).

Although how affective variables, disconfirmation, satisfaction and loyalty relate to each other is broadly known, there are no conclusive findings thus far (Chebat & Michon, 2003). Some authors suggest that disconfirmation affects satisfaction independently from how emotions change satisfaction (Martínez & Martínez, 2007). Others argue that emotions act as mediators (Menon & Dubé, 2000). Among the latter, the cognitive theory of emotions suggests that consumer satisfaction is positively affected by the degree of disconfirmation and the intensity of emotion (Bigné et al., 2005; Wirtz & Bateson, 1999). Lastly, contrast theory supports an unmediated, direct effect of disconfirmation on satisfaction (Hovland, Harvey & Sherif, 1957).

The literature has shown a broad consensus on a two-dimensional character for emotions ever since Russell (1980) proposed pleasure-displeasure and arousal-quiet as the two basic dimensions of emotions. Despite ongoing controversy about the impact of arousal on pleasure, several studies have verified this impact exists, as well as that emotions impact satisfaction (Yüksel & Yüksel, 2007).

2.2 Attractions at the destination as a moderating factor

Extrapolating results between different destination types – or destinations with the same type and different attractions – is further complicated by the varying competitive status of different destination types. Shifting values and preferences among travellers have produced a large market segment that is moving away from traditional seaside destinations. We refer to "traditional" destinations because experts have suggested for some time now that seaside destinations need to restructure by strategically repositioning themselves or diversifying to reverse this apparent decline (Claver, Molina & Pereira, 2007; Meethan, 1998; Aguiló, Alegre & Sard, 2005). Cultural destination tourists, on the other hand, show little interest in products aimed at mass tourism and tend to disapprove of the homogenising effects of globalisation.

Several changes in the tourism industry have elicited a growing interest in destinations with more cultural attractions (Sedmak & Mihalic, 2008). Cultural tourism consists of visiting historical sites and buildings, museums, art galleries, performances, etc., regardless of the main reason for travelling (Richards, 1994; Hughes, 1995). We speak of urban tourism when these cultural tourist attractions are located in a city. In these cases, the destination also includes "urban landscapes" as important attractions, namely well-delimited areas within the city that combine a strong historical identity, a solid cultural heritage, and a variety of shops or leisure options for visitors and residents alike (Snepenger, Murphy, O´Connell & Gregg, 2003; Yüksel & Yüksel, 2007).

Meanwhile, since tourism is considered a consumption experience, perceived quality is, predictably, closely associated with the overall trip experience, even somewhat independently of where the visit specifically occurs (Chen & Chen, 2009). To enhance visitor loyalty, some strategies make a priority of offering high quality and generating experiences that will be perceived as valuable (Lee, Petrick & Crompton, 2007). However, these objectives have proven satisfactory both for cultural destinations (Apostolakis, 2003; Chen & Chen, 2009) and for seaside destinations (Knowles & Curtis, 1999); marketing researchers have not observed that these elements are more or less relevant depending on the destination's attractions.

Emotions are included in the literature, as we mentioned earlier, in those models that examine tourist satisfaction and loyalty. For cultural destinations, how tourists perceive historical landmarks, for instance, is known to be influenced more by affective than by cognitive elements (McIntosh & Prentice, 1999; Pearce, 1984), thus helping to determine tourist satisfaction. Therefore, to analyse urban cultural destinations, researchers must examine the affective elements influencing tourists' perceptions (Edwards, Griffin & Hayllar, 2008; Milman & Pizam, 1995). Meanwhile, if the destination includes the seaside, tourists typically behave more hedonistically and, therefore, are more intent on seeking emotions based on an affective component: pleasure (Carr, 2002). That is why entertainment activities are particularly important for a visit's evaluation (Hughes, 1995).

3.   Objectives and hypothesis

Verifying the universal applicability of the observed relationships for a specific destination is a critical issue for the theory. The question is, can the relationships observed for one destination type be considered applicable to destinations belonging to other types? Furthermore, are the relationships observed in one destination applicable to another of the same type if it has different attractions? The objective of this paper is to answer these questions.  

According to the assumptions made in the literature, including different attractions would apparently influence the way in which a destination image affects tourist satisfaction and loyalty through quality, value, expectations, disconfirmation, and emotions; however, this differential behaviour of the model has not been empirically proven. Therefore, in this study we establish the following hypothesis:

H₁: The behaviour of the posited relationships is influenced by the presence of seaside attractions, and thus validity is not verified for all urban cultural destinations.

4.   Metodology

The questionnaire was based on a seven-level Likert scale. Destination image was measured according to one single-item factor (Bigné et al., 2001). The measurements for the arousal and pleasure constructs were drawn from Bigné et al. (2005); satisfaction was drawn from Oliver (1997); loyalty was measured according to the scale proposed by Zeithaml, Berry and Parasuraman (1996); the scale for expectations was drawn from Murphy et al. (2000); and the scale for disconfirmation was the one used by Oliver & Burke (1999). Lastly, the factors for quality and value were drawn from research by Cronin et al. (2000) (Table 1).

Field work was carried out in the cities of Seville (Spain), York (UK), and Cartagena de Indias (Colombia) over the last quarter of 2010. Selecting destinations of different types had been done previously in the literature (Fyall et al., 2003). Information was collected using a questionnaire and a total of 424 valid questionnaires were obtained for Seville, 195 for York, and 200 for Cartagena de Indias (Table 2). Three destinations were selected so that by comparing the behaviour of the models for different destinations, one could observe the differences between the cultural destinations based on the attractions they had to offer.

York is an established tourist destination in England and has long been acknowledged as a centre for cultural and heritage tourism. Seville is one of the main cultural tourism destinations in Spain. Located on the Caribbean coast, Cartagena de Indias boasts a strategic location for tourism and for industrial and commercial development. 

5.   Results

The scales we used were adapted from those validated in previous works, and whose content we therefore assumed to be valid. Statistical analysis was performed by developing the Structural Equations Model with PLS 3.0 Build 1130 and GeSCA.  

PLS method seeks to predict the value of latent variables based on an estimation of the Ordinary Least Square and on Principal Component Analysis. This approach has certain advantages over covariance-based methods, such as its requirements for the distribution of the variables in the sample, the types of variables, and the sample size (Falk & Miller, 1992; Chin & Newsted, 1999). PLS adapts to prediction and theory development applications, although it can also be used for theory confirmation, as is true of Generalised Structured Components, developed through GeSCA, which has the advantage of providing goodness of fit indices for the models.

Goodness of fit of the different models was determined using the FIT, AFIT, GFI, and SRMR indices. The FIT shows total explained variance of the endogenous variables considered in the model, ranging from 0 to 1. AFIT (Adjusted FIT) is an index that takes into account the model's complexity; it is the most appropriate measure for evaluating alternative models. GFI and SRMR are the classic indices of a model's goodness of fit.

The results achieved in the cities of Seville (FIT= 0.729; AFIT= 0.728; GFI= 0.991; SRMS= 0.191) York (FIT= 0.697; AFIT= 0.693; GFI= 0.992; SRMS= 0.174), and Cartagena de Indias (FIT= 0.682; AFIT= 0.678; GFI= 0.994; SRMS= 0.126) show the adequacy of the model.

The variables used to measure all the constructs showed optimal internal consistency, the loadings being higher than 0.707 for all factors. Therefore, we chose to maintain the initial indicators selected (Table 3).

Convergent validity was established by analysing the Average Variance Extracted (AVE), having determined (Fornell & Larcker, 1981) that the AVE values must be higher than 0.5. In our study, the average variances extracted were above that value, and therefore the convergent validity of the related constructs in the structural model was confirmed. To establish the discriminant validity, the AVE value must be higher than the variance shared by the construct and the other represented constructs.

To simplify the comparison, each element along the main diagonal must be higher than the remaining elements in its row and the corresponding column – correlations between constructs (Barclay, Higgins & Thompson, 1995). The only case for which this rule did not hold was the relationship between arousal and pleasure in the Seville survey.

The behaviour of the constructs included in the model was analysed with a Structural Equations Model (Table 4). The following table shows the significance level for each path and how the vast majority of the examined relationships were accepted regardless of the type of destination we were analysing. It is important to note that the only relationships that had to be rejected were the ones between pleasure and satisfaction for all the destinations, between arousal and satisfaction for urban destinations without seaside attractions, and between disconfirmation and satisfaction, since this hypothesis is only significant in the model for Seville.

The ability to detect the presence or absence of differences between groups and estimate the strength of the moderating effects is important in the studies that attempt to show contingent effects (Qureshi & Compeau, 2009), and do so using the procedure suggested by Chin (2000) for developing multigroup analysis.

Following this procedure, a Student's t-test is calculated according to an equation drawn from a Student's t distribution with m+n-2 degrees of freedom, where S_p is the common estimator for standard error variance, m and n represent the sample size for each group respectively, and SE is the standard error of each path coefficient in the structural model for each group. A multigroup analysis was performed to analyse the existence of differences between the two destination types (with and without sun and seaside attractions).

The table above (Table 5) shows that although many significant differences exist between the multigroup analyses for the three destinations, those differences are reduced when we only analyse two urban cultural destinations without sun and seaside attractions. In this case, differences do exist in the impact of disconfirmation on the dimensions of emotions and the relationships between those emotions. But on the other hand, when analysing the differences between holding costs for urban destinations, we find those differentiate into multiple relationships.

Therefore, we can accept H₁ when considering the influence of tourist attractions that own the destination (the ownership costs in our case) on the relations arising from the model.

6.   Conclusions

To state our conclusions regarding these questions, we will first address those pertaining to the theoretical relationships drawn from the model of behaviour used in the study. Lastly, we will state our conclusions for the model's behaviour depending on the destination type.

We can establish that destination image influences satisfaction, which in turn affects loyalty (Barroso et al., 2007; Chi & Qu, 2008). We can also state that destination image shapes what tourists expect prior to their visit. In addition, we can establish the positive relationship between the degree of so-called expectation disconfirmation, emotion, and satisfaction (Wirtz & Bateson, 1999).

Concerning the mediating role of emotions in the relationship between expectation disconfirmation and satisfaction, the results of the present study only partially verify this mediation. In the realm of emotions, arousal is the only dimension that exerts a significant influence on satisfaction. While arousal also has a strong influence on pleasure, this relationship had already been challenged in previous studies (Martínez & Martínez, 2007; Wirtz & Bateson, 1999). The present study also observed a significant, albeit slight, influence of disconfirmation on loyalty. This effect has recently been challenged (Rodríguez & San Martín, 2008).

Lastly, in the context of the general model, we analysed quality perceived by tourists during their visits. Fyall et al. (2003) and Murphy et al. (2000) identified developing strategies for increasing value and perceived quality as a critical element in tourist destination management. They stated in previous studies that value plays a mediating role in the relationship between quality and satisfaction. It is important to note that this mediation existed in the case of both the urban destinations we analysed, yet was not significant for the destination with sun and seaside attractions. In other words, for destinations offering those attractions, we must add the absence of a significant relationship between value and satisfaction to the weak relationship between quality and value. In keeping with recent studies (Chen & Chen, 2009), we were unable to establish a significant and universally valid effect of quality on tourist loyalty for purely urban destinations; while it does exist for Seville, this is not the case for York.

This lack of overall validity leads to the central question posited in the study: is there a universal logic behind the model we analysed? Specifically, our aim was to determine whether in two tourist destination categories (urban with only cultural attractions on the one hand, and with sun and seaside attractions on the other) the proposed model for observing the relationships between destination and loyalty showed the same empirical behaviour in destinations on different continents.

6.1 Implications for tourism policy and management

The results led us to the conclusion that a common pattern does exist for tourist behaviour (except for relationships between disconfirmation and emotions) in "pure" urban cultural destinations even when those destinations are located in two geographically and culturally distant regions, since there are no significant differences between most of the analysed relationships. This pattern of behaviour cannot be directly extrapolated to destinations with a strong component of seaside attractions.

Although the relationships do exist, their intensity is influenced by the attractions available at the destination. In other words, it is a matter of principle that in strictly urban destinations the model of tourist behaviour is consistent. Therefore, any research into the chain of relationships between destination image, quality, value, expectations, emotions, satisfaction, and loyalty for urban destinations can be extrapolated to similar destinations with highly reliable results.

However, this research cannot be extrapolated to urban destinations with a strong seaside attraction component, even if they also feature important cultural attractions. Therefore, because the theoretical relationships underpinning policies and strategies vary for different kinds of destinations, policies for how to manage tourist destinations must be adapted according to the type of destination involved, and specific strategies and actions to be implemented must be carefully reviewed.

6.2 Limitations and further research

One of the main limitations of the present study is sample size, as well as the duration of the study. In addition, additional tourist destinations should be introduced, especially urban cultural destinations with seaside attractions. It would also be interesting to establish a typology of urban tourist destinations based on the relevance of their cultural attractions as compared to seaside attractions. This would enable us to determine whether the cultural-seaside continuum partly explains the differing behaviour of the model.

In future research, we recommend analysing the possible role of the visitor's culture of origin as a moderating element in the analysed relationships. It has been observed that different cultural origins can affect how expectations are generated, quality is evaluated, and emotions are experienced, all of which are particularly relevant in service marketing.

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Article history:

Submitted: 15 May 2013

Accepted: 17 October 2013