1. Introduction
Since the 1990s, relationship marketing has attracted the attention of academics and professionals (Palmer, 1995), who have focussed on studying the relationships between marketing actors, describing these relationships as contacts between two or more people or between people and objects, symbols and organisations (Gummesson, 1996). However, a relationship strategy can be achieved not only through a mutual interest in maintaining relationships but also by the development of long-term, interdependent relationships, which differentiate this strategy from transactional marketing (Blois, 1996), focussing the attention on a single exchange. Then the relationship approach recognises that retaining and developing relationships over time is critical (He et al., 2018).
Managing customer relationships in service businesses such as tourism is vital due to the intangibility and heterogeneity of the service delivered. This makes organisations more dependent on relationships (Cheng et al., 2008). The challenge is to understand why customers stay longer with a service provider, having relationship quality as a key driver (Walter et al., 2003). Relationship quality refers to the customer’s perceptions and their evaluations of an individual service involving feelings and emotions (Kim and Cha, 2002), which results in the customer intention to rely on providers’ integrity and future performance (Kim et al., 2001). To this end, recognising and fulfilling the needs of people is the main objective of building relationships (He et al., 2018).
Empirical studies applied to relationship marketing in service organisations are scarce (Sin et al., 2006), although the hospitality industry has identified the benefits of establishing relationships with their customers (Oh, 2002). In the late 1990s, the tourism industry introduced customer relationship management (CRM) (Baksi, 2014) in response to greatly increased competition in the tourism market that made developing and maintaining long-term relationships between the relevant stakeholders essential (Radosavljevic and Borisavljevic, 2014). Thus, dealing with customer relationships effectively has become vital to a firms’ survival in today’s competitive markets (Yen et al., 2015). Maintaining ongoing relationships with customers is crucial for sustaining a competitive advantage (Kim et al., 2006), as it is less expensive to retain customers than to acquire new ones (Kim and Cha, 2002). As a result, research focussed on relationship marketing cause-effect models in tourism has increased noticeably, although these models have mainly been applied in the hotel industry (Radosavljevic and Borisavljevic, 2014).
Relationship quality appears as an emerging concept in the literature on tourism relationship marketing (Moliner et al., 2007). Theory about this topic has been overlooked (He et al., 2018), and limited empirical research in this context focusses on the predictors and outcomes of relationship quality (Kim et al., 2006).
An explanatory model of tourism destination loyalty, based on a relational approach to marketing, was applied in the setting of rural tourism destinations, as these are understood as an interesting context. According to Maggon and Chaudhry (2015):
Maintaining relationships with customers and employees is a fundamental activity for almost every hospitality organization, whether it is a small or large hotel, a travel agency, a restaurant, a casino, or an airline (p. 54).
Therefore, it should be possible to confirm the importance of applying the relational approach of marketing, especially in rural tourism destinations and companies which are generally small-sized organisations. According to Van Zyl and Mathur-Helm (2007), small tourism companies can benefit from developing sustainable relationships with stakeholders, thereby improving their business performance.
Thus, this paper’s objective is to explore the role of relationship quality in tourism destination loyalty enhancement, using an innovative approach assented in trust, attachment and satisfaction with relationships, in the specific context of rural tourism, a type of tourism in which relationships can be fostered. The study described sought to determine the capacity of relationship variables to generate loyalty, which helps to foster ties between tourists and destinations. Relationship quality development in this framework can be understood as a tool to increase the profitability of the benefits that rural tourism offers to these particular destinations and their small-sized organisations.
2. Relationship marketing and its applications to tourism destinations: the relevance of relationship quality and destination loyalty
Quality is a key concept in tourism because it is understood as an indicator of success and profitability in businesses (Rivera and Croes, 2010). In the 1980s, the research on quality in tangible goods was delt with in depth. However, some difficulties existed regarding the definition and measurement of services. To complete this approach, it was necessary to take into account its main characteristics, those being intangibility, heterogeneity and inseparability (Parasuraman et al., 1985). According to Žabkar et al. (2010) quality in tourism is “created by the processes of service delivery (e.g. friendliness, courtesy, efficiency, reliability, staff competence) and outcomes of services (e.g. accommodation, food, leisure facilities)” (p. 538). In this sense, Murphy et al. (2000) affirm that at the moments of truth the encounter with the destination and its service infrastructure leads the traveller to an overall perception of service quality. The more positive the encounter with the service, the greater the perceived quality. According to Su et al. (2016), service quality is conceived as an overall evaluation of a firm performance, whereas relationship quality is considered as a strategic orientation centred on enhancing customer relationships.
The tourism sector has been in the vanguard of those sectors adopting a relational approach. However, limits can be found on this strategy’s application in tourism. Clients may not want a relationship with the service provider. Many organisations cannot apply loyalty strategies when they already operate in markets with small profit margins. Some tourist segments are not attracted by the idea of visiting a place for the second time, and, finally, the intention to create relationships with clients can be blocked by organisational structures, processes and values that are not customer-oriented, as well as a lack of cooperation between organisations (Palmer and Mayer, 1996). Sin et al. (2006) stress that relationship marketing is suitable for the hotel industry, due to its close interaction with customers. However, tourism destinations have taken advantage of the benefits offered by adopting a relationship strategy, although not without encountering problems, such as those described by Palmer and Mayer (1996). Even so, a good understanding of how relationships can be developed to create destination loyalty is important to both researchers and practitioners (Su et al., 2017). Regarding destination marketing, there is a lack of conceptual application of the relationship management paradigm (Choi and Cai, 2017).
Along these lines, Murdy and Pike (2012) developed a study on the introduction of a relationship marketing approach in international tourism destinations. They identified three aspects that need improvement. These are:
clarifying objectives of marketing to encourage visitor acquisition and retention;
upgrading interdepartmental communication; and
supporting top management.
The cited authors also found areas in which destination managers are doing well:
rapid responses to visitors’ requests;
employees willing to help tourists responsibly;
fast service;
an understanding of the needs of key customers;
proper treatment of key clients; and
efforts to find out what customers need.
Overall, these positive points overcome any drawbacks regarding the performance of relationship marketing strategies in tourism destinations.
Murdy and Pike’s (2012) findings reveal that tourism destinations can create long-lasting relationships with high-value tourists. Similarly, Su et al. (2017) claim that the relationship marketing approach is vital for tourism destinations. In addition, Pike et al. (2011) suggest that research on the repeated behaviour of tourists in destinations should be done to foster greater satisfaction and loyalty, which translate into profits.
Similarly with the conceptualization of products’ and services’ quality, relationship quality arises (Lo and Im, 2014), which is generally accepted as the key driver for developing loyalty (Walsh et al., 2010).
In this context, Maggon and Chaudhry (2015) recently developed a study on the state of the art of relationship marketing and CRM research published in top tourism journals from 2001 to 2013. The results show that relationship quality is a key theme in tourism research, scarcely applied to destinations.
The literature review done in previous studies of the determinants of loyalty to destinations, accommodations and other tourism products (Campón et al., 2012) was updated for the present study within the area of tourism destinations and related topics. This review made it clear that relationship constructs such as trust and commitment have seldom been taken into account. Su et al. (2017) also observed this gap, identifying a lacuna in the published empirical research on relationship variables and destination loyalty.
According to Morgan and Hunt (1994), the presence of commitment and trust is fundamental to the success of relationship marketing. The need for commitment and trust are the key to motivating marketing managers to cooperate with exchange partners, to resist attractive short-term solutions and to be cautious about believing that all parties avoid acting opportunistically. Therefore, when both commitment and trust are present, efficiency, productivity and effectiveness are enhanced. According to Gundlach et al. (1995), commitment between all parties is an important sign of relationship quality and lays the foundation for building trust.
Relationship quality theory proposes that customers offer value over the time they interrelate with an organisation and vice-versa (He et al., 2018). However, the discussion regarding the conceptualisation and the measurement of relationship quality is still unsolved (Cheng et al., 2008; Lo and Im, 2014). Many authors have suggested a few definitions, but there is no agreement about which is the most appropriate, and the constructs for its measurement have significantly increased (Loureiro and Cunha, 2017). Thus, some authors suggest that relationship quality lacks both formal definition as well as consensus about what dimensions involve. It is recognised that it is formed as a higher-order construct (Su et al., 2016).
Garbarino and Johnson (1999) define relationship quality as an overall evaluation of the strength of relationships. Cheng et al. (2008) add that relationship quality is achieved when the customer’s needs and wants are fulfilled. According to Radosavljevic and Borisavljevic (2014), relationship quality starts with customers’ perceptions and evaluations of criteria such as respect, sincerity, kindness, support and help given to buyers. In short, the concept “captures the essence of relationship marketing” (Jap et al., 1999, p. 304).
Regarding the measurement of relationship quality, depending on which author is consulted, it is shaped by commitment, trust and satisfaction (Tsai, 2015; Walsh et al., 2010; Yen et al., 2009) or a combination of these. Lo and Im (2014) affirm that relationship quality is mainly composed of trust, commitment and satisfaction, and these three constructs are frequently used as its higher-order dimensions in hospitality research. The present study, therefore, chose to designate relationship quality as a combination of the three variables.
Although the literature considers the construct of commitment a crucial element in relationship quality, Lee et al. (2007) offer a theoretical rationale based on which commitment can substitute for place attachment when applied to a place or destination, a conceptualisation that was adopted in the present study. Along these lines, Chen and Phou (2013) equate relationships with tourism destinations with the concepts of satisfaction, trust and attachment.
Therefore, based on these previous studies, a gap needs to be filled in the existing literature on loyalty to tourism destinations with a focus on relationship marketing by developing a model that involves relationship quality. According to Su et al. (2016), relationship quality is accepted as an important antecedent of post-purchase behaviour and a key driver to develop loyal customers. Thus, the model proposed in this study tries to shed new light on the effects of relationship quality in enhancing destination loyalty.
3. The relationship approach in rural tourism: is it possible to achieve loyal rural tourists?
The tourism industry has benefited from relationship marketing (Oh, 2002), but its application to rural tourism has been scarce, although authors such as Thomas et al. (2011) have proposed more research on tourism marketing for SMEs, as rural tourism organisations are these. Loureiro (2010) emphasises that rural tourism has to face the challenges of an increasingly competitive market, so it is interesting to maintain loyal visitors to guarantee the long-term success of rural tourism organisations and destinations.
The question that can arise at this point is if rural tourism has the possibility to implement relationship marketing. First, Palmer and Mayer (1996) underline the special ability that small, local and family-run businesses have in developing relational behaviours. Small-size and self-managed companies, which is the typical business model in rural tourism, achieve emotional loyalty more easily than larger companies. Second, McKercher and Guillet (2011) argue that short-haul travellers seek the familiarity of known destinations, which could explain higher levels of intention to revisit a place. This is an important factor in rural tourism, as stays are usually short (Cánoves et al., 2005b). Finally, McKercher et al. (2012) affirm that tourists who appreciate diversity in their trips look for different experiences in each occassion. Very diverse activites can be experienced at different locations at the same destination. In this line, rural tourism can satisfy the wonderlust of the modern traveller, as rural areas usually boast a wide variety of micro-destinations and experiences.
The study of loyalty in rural tourism is an area of great interest that needs additional research (Loureiro and Kastenholz, 2011). Loureiro and Miranda (2008) contend that the findings of previuous researches on destination loyalty are not helpful for rural tourism managers because the special features of this type of tourism are not included in these studies.
4. Theoretical model and research hypotheses
The research on relationship quality in the hospitality industry is scarce (Castellanos-Verdugo et al., 2009), while relationship quality has been widely studied as an antecedent of behavioural intentions (Han and Hyun, 2013; He et al., 2018; Su et al., 2016). Hospitality literature reveals that high levels of relationship quality lead to high levels of satisfaction, trust and commitment (Lo and Im, 2014) as well as loyalty, that is considered as an essential element for a succesfull relationship marketing strategy (Kim et al., 2006).
The sections below detail the theoretical model and research hypotheses. The discussion places a special emphasis on the definition of the variables that make up relationship quality and their relationships with overall satisfaction and destination loyalty. To obtain a more comprehensive result of the relationships established in the model, their hypotheses were described according to their variables’ dimensions.
Yüksel et al. (2010) define place attachment as “the process by which humans form emotional bonds” (p. 275). This concept is considered a key element in a full understanding of tourists’ intentions and behaviours (Stylos et al., 2017) because it can increase visitors’ willingness to return to destinations (Chubchuwong et al., 2015).
The importance of destination attachment has meant that this concept has attracted the interest of researchers (Reitsamer et al., 2016), but contradictory approaches have been used to analyse the dimensions of place attachment. The most recognised measurement approach to this concept includes two dimensions:
place identity, which refers to emotional attachment; and
place dependence, which serves as functional attachment (Stylos et al., 2017; Williams and Vaske, 2003).
The present study followed this approach. The Social Identity Theory can also offer support for this construct. This theory provides a framework to understand group participation in many fields and a better comprehension of visitors’ attitudes and behaviours in tourism, as tourists’ recommendations to visit a destination can become a reliable information source that promotes travel decisions (Chiang et al., 2017).
Yüksel et al. (2010) and Prayag and Ryan (2012) confirmed the mediating effect exercised by overall satisfaction between attachment and loyalty/behavioural intentions, as revealed by revisits and recommendations. Based on these assertions, the first hypothesis in the present study was defined as:
Destination attachment has a positive effect on overall satisfaction.
Destination identification has a positive effect on overall satisfaction.
Destination dependence has a positive effect on overall satisfaction.
The experiential value offered by destinations provides a suitable context in which to develop loyalty (Su et al., 2017). According to Oppermann (2000), “destination loyalty essentially places the emphasis on a longitudinal perspective, looking at lifelong visitation behaviour of travellers rather than just at a cross-sectional perspective” (p. 78). However, an inherent problem in the analysis of destination loyalty is measuring the length of time for each purchase period and determining the length of time that indicates a tourist is loyal (Oppermann, 2000). This is why loyalty is measured not only by repeated visits but also by recommendations to others (Chen and Phou, 2013; Mechinda et al., 2009; Phillips et al., 2013; Prayag and Ryan, 2012; Su et al., 2017).
A variety of empirical evidence supports positive impacts on the relationship between attachment and loyalty (Chen and Phou, 2013; Mechinda et al., 2009; Prayag and Ryan, 2012; Tsai, 2012; Xu and Zhang, 2016; Yüksel et al., 2010). This led to the development of the second hypothesis of the present study:
Destination attachment has a positive effect on loyalty.
Destination identification has a positive effect on loyalty.
Destination dependence has a positive effect on loyalty.
In the specific case of satisfaction with tourism destinations, Su et al. (2017) conceptualise satisfaction as “a tourist’s overall evaluation of a destination”.
According to Choo and Petrick (2012), few studies have examined the interpersonal relationships that clients experience when receiving services. The cited authors’ research results indicate a need to expand the scope of customer-focussed relationship marketing to include all relationships produced by interactions with other parties involved in providing services, as these are significant in this context. Kim et al. (2006) highlight that relationship marketing drives long-term interactive relationships between the service provider and the customer.
Another important aspect on which the success of tourism relies is the hospitality of residents and their goodwill (Gursoy et al., 2002). Residents’ unfriendly behaviour towards visitors can be a drawback, while kind attitudes can generate good experiences for tourists (Almeida-García et al., 2016).
Choo and Petrick (2012) sought to examine the interaction between satisfaction with relationships with providers and overall satisfaction and succeeded in proving the existence of this interaction. Alegre and Cladera (2009) ascertained the significance of the relationship between satisfaction with hospitality and overall satisfaction. Based on these findings, the third hypothesis in the present study was formulated as follows:
Satisfaction with relationships has a positive effect on destination overall satisfaction.
Satisfaction with relationships with tourism service providers has a positive effect on destination overall satisfaction.
Satisfaction with relationships with residents has a positive effect on destination overall satisfaction.
The proposal of two dimensions related to satisfaction with relationships with tourism service providers and with residents implies testing the well-known and accepted relationship between satisfaction and loyalty (Chen and Phou, 2013; Mechinda et al., 2009; Su et al., 2017; Yüksel et al., 2010) in a more specific context. This led to the fourth research hypothesis:
Satisfaction with relationships has a positive effect on destination loyalty.
Satisfaction with relationships with tourism service providers has a positive effect on destination loyalty.
Satisfaction with relationships with residents has a positive effect on destination loyalty.
Trust is one of the most widely studied and accepted concepts in relationship marketing (Tsai, 2015). Su et al. (2017) define trust “as the belief that a party will fulfil his or her obligations in the relationship and specifically examine trust toward destination service providers in a tourism context” (p. 184). Few studies have specifically studied trust in tourism destinations. For example, this variable’s antecedents were identified in Chen and Phou (2013) and Tsai’s (2012) research. Some studies also have examined trust in terms of tourism service providers (Su et al., 2017; Yen et al., 2009). The present study chose to evaluate these two perspectives to deepen the understanding of this variable in the context of loyalty and tourism destinations.
The link between trust and satisfaction is clear in the concept of relationship quality (Yen et al., 2009). Chen and Phou (2013) and Yen et al. (2009) also examined the influence of satisfaction on trust. Given these findings, the fifth hypothesis was formulated as follows:
Overall satisfaction has a positive effect on trust.
Overall satisfaction has a positive effect on destination trust.
Overall satisfaction has a positive effect on trust in tourism service providers in destinations.
The direct impact trust has on loyalty also needs to be examined, to develop relationship strategies that achieve their central objective of greater loyalty. Authors such as Chen and Phou (2013) and Yen et al. (2009) found proof of the direct impact of trust on loyalty. In particular, Su et al.’s (2014) and Su et al.’s (2017) studies found empirical support for the effects of tourists’ trust in destination service providers on word of mouth but not on revisit intentions. And Kumar and Kaushik (2017) obtained empirical evidence for the relationship between destination trust and destination loyalty. The sixth hypothesis was based on these results:
Trust has a positive effect on destination loyalty.
Destination trust has a positive effect on destination loyalty.
Trust in tourism service providers has a positive effect on destination loyalty.
Relationship quality is an important outcome of behavioural intentions and, from the consumer’s perspective in tourism, it tends to be associated with tourists’ loyalty to the destination (Hopeniené and Rutelioné, 2016). The relationship between overall satisfaction and loyalty has been widely studied, including in the studies of those factors generating loyalty to tourism destinations including some relationship variables. These include, for example, research in the context of attachment (Prayag and Ryan, 2012; Yüksel et al., 2010) or trust (Chen and Phou, 2013; Mechinda et al., 2009; Su et al., 2017; Yen et al., 2009). However, this relationship has only rarely been examined in the context of rural tourism destinations (Phillips et al., 2013). Given these theoretical constructs, the seventh hypothesis in the present study was formulated as follows:
Overall satisfaction has a positive effect on loyalty to rural tourism destinations.
Figure 1 depicts the theoretical model.
5. Methodology
This study used a quantitative methodology based on an on line survey conducted in Spain. According to data collected by Spain’s National Institute of Statistics, since 2001 to 2017, rural tourism has tripled in size in terms of supply and demand, experiencing an extensive expansion that makes it a suitable setting for the present research. In Spain, rural tourism emerged as a response to the stagnation of the traditional model of sun and sea. As a consequence, rural areas have experienced the benefits of tourism. Rural tourism development allowed for a valorisation of local natural and cultural heritage, while offering new tourism destinations in line with a changing demand made by travellers who seek tranquillity, along with motivating, authentic, educative and personalised experiences during their holidays (Cánoves et al., 2005a).
The scales used to test this model were inspired and validated by previous studies. These scales were adapted in this study for the context of rural tourism. They were next validated in a pretest with twenty researchers and professionals specialising in this area (Table I).
The questionnaire was designed using the scales cited in Table I. Seven-point Likert scales were applied as they are recommended by Cummins and Gullone (2000). Participants were asked to answer the questions keeping in mind their last rural tourism destination visited.
Before the questionnaire’s final distribution, a pilot study was done with a small, selected subsample of the target population to confirm definitively the corrections made in this instrument. A digital version of the questionnaire was distributed by e-mailing, social networks, a website and a blog. The reasons why this research used an on line survey lies in the advantages pointed out by Hung and Law (2011) regarding the geographical coverage and the possibility of identifying specific audiences, such as tourists who usually engage in rural tourism. The authors also mention some limitations of this method, which are the sample representativeness, the low response rate, technical difficulties and inactive or inaccurate e-mail addresses. Another problem identified by Baena et al. (2010) is if people answer the on line questionnaire more than once, considerably altering the survey’s results. According to Reips (2002), it is estimated that the probability of occurrence of this problem is less that 3 per cent in the majority of the studies, which is not a threat for the research’s reliability. Taking into account these limitations, it was understood that the pros outweigh the cons, and the risk that could be introduced by the usage of an on line method is assumable.
This study’s population universe was composed of people who regularly participate in rural tourism (i.e. at least once every two or three years). The fieldwork was done from 22 April 2013 to 18 June 2013, resulting in a non probability convenience sample of 464 valid completed questionnaires. The sample reached a great geographical representativeness, with all the Spanish regions being represented with the exception of one.
Regarding the respondents’ profile, 41.2 per cent are men and 58.8 per cent women. Respondents between 26 and 55 years of age made up 85.6 per cent of the sample. In addition, half of the sample (49.8 per cent) participates in rural tourism regularly (“once or twice a year”), which confirms this sample’s suitability.
The analysis of the proposed model was carried out based on an evaluation of structural equation modelling using the partial least squares method, as this is particularly appropriate for exploratory studies with predictive goals, as is the case of the present research (Hair et al., 2011).
6. Results
The measurement model contains constructs made up of reflective indicators that, therefore, needed to be evaluated for reliability and validity (Hair et al., 2011). The analysis of individual reliability showed that the factor loadings have a weight above 0.707 (Barclay et al., 1995; Hair et al., 2011), with the exception of DDE1, DDE6, OVS6, LOY1 and LOY2. However, this guideline does not need to be rigidly followed in the first stages of scale development or the times at which these are applied in different contexts, so loadings of 0.50 or 0.60 can be considered acceptable (Barclay et al., 1995) (Table II).
Table III shows that the constructs’ internal consistency was verified, falling within the parameters considered acceptable (Nunnally and Bernstein, 1994). The proposed model also showed convergent validity, as the average variance extracted (AVE) values are above 0.5 (Hair et al., 2011). The analysis of discriminant validity was done by demonstrating that the correlations between constructs are lower than the square root of the AVE which is shown diagonally and in italics (Barclay et al., 1995) (Table III).
To evaluate the structural model, the R2 was analysed for each dependent construct. The statistical significance of the paths was also analysed using bootstrapping (Hair et al., 2011).
The proposed model’s dependent constructs possess a moderate to substantial explanatory capacity for overall satisfaction (62.8 per cent) and a moderate capacity for destination trust (49.8 per cent), trust in tourism service providers (41.0 per cent) and loyalty (58.6 per cent) (Table IV).
The variance explained in an endogenous construct by another latent variable was also presented following Falk and Miller (1992) (Table IV).
An analysis of the statistical significance of the paths revealed that the majority of the research hypotheses developed are supported by the results, with the exception of H4A, H4B and H6B (Table IV and Figure 2).
The theoretical model proposed in this study showed a good fit in the measurement model, and it was empirically validated in relation to the hypotheses developed, except for H4A (RPS → LOY), H4B (RRS → LOY) and H6B (TPR → LOY). The model can explain 62.8 per cent of overall satisfaction and 58.6 per cent of destination loyalty, revealing a moderate to substantial explanatory capacity of its relationships. Overall satisfaction is shown to unify all the effects relationship quality has on loyalty.
Regarding the variables included in relationship quality, trust and overall satisfaction are strongly linked, as indicated by the value of β for the relationships OVS → TDE (β = 0.7054***) and OVS → TPR (β = 0.6405***). In addition, the two variables contribute to the explained variation of both path dimensions, although more to trust in destinations (49.8 per cent) than to trust in tourism service providers (41.0 per cent). Destination attachment has a significant impact on the formation of overall satisfaction, as shown in previous studies (Prayag and Ryan, 2012; Yüksel et al., 2010), contributing more to destination dependence (10.5 per cent) than to destination identification (5.6 per cent). The influence of these dimensions of attachment on loyalty also proves to be relevant, which agrees with other research (Chen and Phou, 2013; Mechinda et al., 2009; Prayag and Ryan, 2012; Tsai, 2012; Xu and Zhang, 2016; Yüksel et al., 2010), with destination dependence contributing 16.3 per cent to loyalty and destination identification 5.8 per cent.
While the results confirm the impact of destination trust in destination loyalty, an insight in accordance with Kumar and Kaushik’s (2017) study, trust in tourism service providers is not shown to have the expected value regarding its impact on loyalty. This last differs from the results obtained by Su et al. (2014) and Su et al. (2017). As trust is a key variable in relationship strategies and, according to Palmer (1994), loyalty is their primary objective, a greater weight would be expected for trust in terms of loyalty – in the dual dimensions proposed in the present study.
The case of satisfaction with relationships with both tourism service providers and residents is paradigmatic, as these are shown to be significant in terms of their relationship with overall satisfaction and quite important in terms of satisfaction with relationships with residents (39.1 per cent), as these are the primary antecedents of satisfaction. Although previous studies did not include satisfaction with relationships with residents as an antecedent of overall satisfaction – or did so in a quite limited way – this variable appears to be an appropriate choice when explaining tourists’ satisfaction with destinations.
However, these dimensions of satisfaction do not turn out to be significant in their influence on loyalty. In this sense, further reflection is needed on why relationships and trust in tourism service providers do not encourage greater destination loyalty. The answer to this question might be found in the context in which this research took place – rural tourism. As indicated by Polo et al. (2012), rural tourism companies tend to be customer-oriented due to their strategy of specialising in a niche market. However, one explanation of the lack of support for H4A, H4B and H6B is a possible lack of orientation towards relationships in tourism-oriented small and medium-sized and micro-enterprises operating in rural tourism destinations. Regardless, relationships with residents have been shown to be significant in the creation of overall satisfaction, although they do not contribute to destination loyalty in rural tourism destinations.
Regarding the relationship between overall satisfaction and loyalty, H7 has empirical support in rural tourism contexts, a result that is consistent with a long list of studies in other contexts (Mechinda et al., 2009; Prayag and Ryan, 2012; Williams and Soutar, 2009; Yüksel et al., 2010). This is the most important causal factor in the creation of loyalty because of its capacity to explain 27.4 per cent of variation in loyalty. However, the direct effect of overall satisfaction on loyalty must be supplemented by the indirect effects of the variables that make up relationship quality.
In light of these results – and despite the non-significant relationships revealed – the results obtained confirm the structure of the proposed theoretical model, including the impact of relationship quality on overall satisfaction and loyalty. In addition, the findings have a moderate to substantial explanatory power for the variables. This finding could contribute to an improved understanding of the phenomenon of loyalty to tourism destinations, stimulating further reflection about rural tourism destinations.
7. Conclusion
The present research examined the influence of relationship quality (i.e. trust, attachment and satisfaction with relationships) on overall satisfaction and destination loyalty, more specifically, in rural tourism destinations. The results confirm that the model has a substantial to moderate explanatory capacity for overall satisfaction and loyalty, in which overall satisfaction acts as a mediator between the variables that make up relationship quality in reference to loyalty. These variables are relevant in the creation of overall satisfaction and the direct generation of loyalty – with the exception of satisfaction with relationships and trust in tourism service providers.
The main theoretical contributions of this study are threefold. First, the significant role played by relationship quality regarding destination loyalty, studied in detail in this model, can be considered the main contribution of this work. These results are in accordance with Su et al.’s (2017) findings, which underline the importance of managing quality relationships to create loyalty. Thus, this model provides theoretical and empirical support to enhance destination loyalty, specifically in the context of rural tourism, through the relational approach of marketing. Another contribution is the proposal of an innovative approach to the measurement of satisfaction and trust, that is more appropriate to explain relationship marketing in the context of rural tourism. Finally, a novel approach to understanding relationship quality in tourism destinations was proposed. Based on the theoretical rationale provided by Lee et al. (2007) and Chen and Phou (2013) commitment was substituted by attachment. The results offer empirical support to apply this innovative tridimensional measurement of relationship quality to tourism destinations.
Regarding practical implications, destination managers should take into account the results obtained in this study and introduce them in their tourism development programmes in rural tourism contexts, giving relationships a special role. Phillips et al. (2013) highlight that information about intention of returning or recommending a rural tourism destination is very relevant for supporting the marketing planning or for having an effective usage of the limited resources.
According to Maggon and Chaudhry (2015) introducing CRM strategies, which root in relationship marketing, could improve “profitability in the long run by shifting from transaction-based marketing” (p. 55). Destination managers need to be able to count not only on entities that coordinate initiatives at the level of destination and marketing strategies but also on the involvement of institutions, businesses and residents, all of which take into account the relational approach of marketing as a key driver. Therefore, destination managers have to take into account the development of relationship quality. Su et al. (2017) call attention to the importance of monitoring satisfaction and trust as a way to improve tourists’ experiences of high-quality relationships. Moreover, the cited authors propose creating a tourist-centred service culture based on the relationship marketing approach to foster sustainable competitive advantages for tourism destinations. On the other hand, Li et al. (2010) found that tourists who visit rural tourism destinations are more motivated by affective features than by physical ones. Therefore, rural tourism communication strategies should focus more on emotional elements than on natural and cultural attractions.
The main limitations of this research arise from the scarcity of works which aim to understand relationship quality in tourism destinations. More studies of this type should continue to delve into those factors that generate destination loyalty and, more specifically, loyalty to rural tourism destinations. In addition, this study was applied to Spain. The cultural features of the country, as well as the particularities of its rural tourism development could introduce some biases.
To broaden results, it should be applied in other tourism destinations, products, services and experiences, in which the contact between the customer and the provider is high. Also longitudinal studies could be relevant to better understand the relationships that tourists establish with rural tourism destinations, monitoring their behaviours through CRM tools. In addition, new relationships could be tested using other relevant variables to understand destination loyalty (e.g. authenticity, quality of life, involvement, etc.), as well as delving into the relationships established in the present model, and into the knowledge about the relationships between the variables that build up relationship quality and its dimensionality. In short, it should be relevant to continue researching into the relationships that emerge between tourists and destinations to promote destination loyalty and, therefore, the profitability that tourists offer over the time.
The dissemination of this research has the support of the European Regional Development Fund, European Social Fund of the European Union, conceded within the framework of the programme Support for the Implementation of Research Activities and Technological Development, Dissemination and Transfer of Knowledge by Extremadura Research Groups, which is managed by the Council of Economy and Infrastructure of the Regional Government of Extremadura, Spain (Reference No. GR15170).
Theoretical model
Graphical results of model assessment
Scales
| Variable | Dimension | Based on |
|---|---|---|
| Attachment | Destination identity | Williams and Vaske (2003) |
| Destination dependence | Williams and Vaske (2003) | |
| Satisfaction with relationships | With tourism service providers | De Wulf et al. (2001) |
| With residents | Alegre and Cladera (2009), Campo-Martínez and Garau-Vadell (2010). Proposal of two indicators | |
| Trust | In the destination | Chen and Phou (2013) and Tsai (2012). Proposal of three indicators based on Ganesan (1994) (two components of trust: credibility and benevolence) and Tsai (2012) |
| In tourism services providers | Verhoef et al. (2002) | |
| Overall satisfaction | – | Williams and Soutar (2009), Yüksel et al. (2010). Proposal of one indicator based on Oliver (1997) |
| Loyalty | – | Mechinda et al. (2009) |
Measurement model assessment
| Constructs and indicators | Loading |
Composite reliability | AVE |
|---|---|---|---|
| Destination identity_DID | 0.9473 | 0.7499 | |
| DID1_I feel it is a part of me | 0.8609*** | ||
| DID2_It is very special to me | 0.8792*** | ||
| DID3_I strongly identify with it | 0.8867*** | ||
| DID4_ I am very attached to it | 0.8987*** | ||
| DID5_Visiting it says a lot about who I am | 0.8102*** | ||
| DID6_It means a lot to me | 0.8572*** | ||
| Destination dependence_DDE | 0.8643 | 0.5155 | |
| DDE1_It is the best place for engaging in rural tourism | 0.6591*** | ||
| DDE2_No other rural tourism destinations can compare to it | 0.7357*** | ||
| DDE3_I prefer to visit that destination more than any other | 0.7613*** | ||
| DDE4_For me it is more important to do rural tourism there, than in any other place | 0.7558*** | ||
| DDE5_It is an irreplaceable place | 0.714*** | ||
| DDE6_I don’t have the same enjoyment in a similar place | 0.676*** | ||
| Relations with tourism service providers satisfaction_RPS | 0.9102 | 0.7718 | |
| RPS1_I have a high-quality relationship with the tourism enterprises | 0.8815*** | ||
| RPS2_The tourism enterprises treat regular customers especially | 0.8411*** | ||
| RPS3_I am satisfied with the relationship I have with tourism enterprises | 0.9115*** | ||
| Relations with residents satisfaction_RRS | 0.9356 | 0.7842 | |
| RRS1_I receive kind treatment as a customer from residents | 0.8888*** | ||
| RRS2_I am satisfied with the local people’s hospitality | 0.8994*** | ||
| RRS3_I am pleased with the residents’ willingness to solve problems, incidents or setbacks that I could have | 0.8811*** | ||
| RRS4_I am satisfied with the residents willingness to offer information | 0.8727*** | ||
| Trust in the destination_TDE | 0.9278 | 0.7199 | |
| TDE1_Sense of trust | 0.8524*** | ||
| TDE2_Confidence and security | 0.8599*** | ||
| TDE3_Sense of security that I will find everything I need in my stay | 0.8566*** | ||
| TDE4_Sense of security that I will find all the information needed for my trip | 0.8081*** | ||
| TDE5_Sense of security that I will enjoy a pleasant experience | 0.864*** | ||
| Trust in tourism service providers_TPR | 0.9601 | 0.8574 | |
| TPR1_They keep their promises | 0.9169*** | ||
| TPR2_They put the customer’s interests first | 0.934*** | ||
| TPR3_They keep the promises that they make to me | 0.9312*** | ||
| TPR4_They provide a good service | 0.9215*** | ||
| Overall satisfaction_OVS | 0.9403 | 0.7266 | |
| OVS1_I had a good experience | 0.8716*** | ||
| OVS2_I made a wise choice | 0.9098*** | ||
| OVS3_I found exactly the rural tourism destination that I was looking for | 0.8803*** | ||
| OVS4_I feel satisfied with my decision to visit it | 0.8992*** | ||
| OVS5_My expectations were fulfilled at all times | 0.883*** | ||
| OVS6_I feel it is a close-to-ideal destination | 0.6393*** | ||
| Loyalty_LOY | 0.8584 | 0.5561 | |
| LOY1_I consider myself a loyal visitor | 0.5628*** | ||
| LOY2_I will visit it in my next rural tourism trip | 0.5822*** | ||
| LOY3_I will visit the destination again in the future | 0.8089*** | ||
| LOY4_I will recommend it to people who ask my advice | 0.8632*** | ||
| LOY5_I will tell other people positive things about it | 0.8517*** |
Notes:aCritical t-values: *p < 0.05; **p < 0.01;
***p < 0.001; nsnot significant (based on t(4999), one-tailed test); t(0.05;4999) = 1.645; t(0.01;4999) = 2.327; t(0.001;4999) = 3.092
Discriminant validity analysis
| DID | DDE | RPS | RRS | TDE | TPR | OVS | LOY | |
|---|---|---|---|---|---|---|---|---|
| DID | 0.8660 | |||||||
| DDE | 0.627 | 0.7180 | ||||||
| RPS | 0.4375 | 0.4687 | 0.8785 | |||||
| RRS | 0.4152 | 0.4895 | 0.5687 | 0.8856 | ||||
| TDE | 0.42 | 0.5414 | 0.5282 | 0.6112 | 0.8485 | |||
| TPR | 0.3638 | 0.4367 | 0.5629 | 0.566 | 0.6686 | 0.9260 | ||
| OVS | 0.504 | 0.5741 | 0.5683 | 0.7401 | 0.7054 | 0.6405 | 0.8524 | |
| LOY | 0.5282 | 0.6293 | 0.4524 | 0.561 | 0.6061 | 0.5151 | 0.7022 | 0.7457 |
Note:Legend: DID-Destination identity, DDE-Destination dependence, RPS-Relations with tourism service providers providers satisfaction, RRS-Relations with residents satisfaction, TDE-Trust in the destination, TPR-Trust in tourism service providers, OVS-Overall satisfaction, LOY-Loyalty
Effects on endogenous variables and structural model results
| Hypothesis | R2 | Direct effect (β) | Correlation | Explained variance (%) | t-value (bootstrap)a | Support |
|---|---|---|---|---|---|---|
| Overall satisfaction | 0.6281 | 62.8 | ||||
| H1A: DID → OVS | 0.1115** | 0.504 | 5.6 | 2.5025 | Yes | |
| H1B: DDE → OVS | 0.1832*** | 0.5741 | 10.5 | 4.3593 | Yes | |
| H3A: RPS → OVS | 0.1331** | 0.5683 | 7.6 | 3.0536 | Yes | |
| H3B: RRS → OVS | 0.5284*** | 0.7401 | 39.1 | 12.8355 | Yes | |
| Trust | ||||||
| H5A: OVS → TD | 0.4975 | 0.7054*** | 0.7054 | 49.8 | 26.5797 | Yes |
| H5B: OVS → TP | 0.4102 | 0.6405*** | 0.6405 | 41.0 | 19.9731 | Yes |
| Loyalty | 0.5861 | 58.6 | ||||
| H2A: DID → LOY | 0.1106** | 0.5282 | 5.8 | 2.5732 | Yes | |
| H2B: DDE → LOY | 0.2583*** | 0.6293 | 16.3 | 5.6433 | Yes | |
| H4A: RPS → LOY | −0.04ns | 0.4524 | −1.8 | 1.0503 | No | |
| H4B: RRS → LOY | 0.0249ns | 0.561 | 1.4 | 0.488 | No | |
| H6A: TDE → LOY | 0.1263** | 0.6061 | 7.7 | 2.3756 | Yes | |
| H6B: TPR → LOY | 0.036ns | 0.5151 | 1.9 | 0.773 | No | |
| H7: OVS → LOY | 0.3903*** | 0.7022 | 27.4 | 5.8933 | Yes |
Notes:Legend: DID-Destination identity, DDE-Destination dependence, RPS-Relations with tourism service providers satisfaction, RRS-Relations with residents satisfaction, TDE-Trust in the destination, TPR-Trust in tourism service providers, OVS-Overall satisfaction, LOY-Loyalty;
aCritical t-values: *p < 0.05;
**p < 0.01;
***p < 0.001;
nsnot significant (based on t(4999), one-tailed test); t(0.05; 4999) = 1.645; t(0.01; 4999) = 2.327; t(0.001; 4999) = 3.092
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