The tourist loyalty index: A new indicator for measuring tourist destination loyalty?

Abstract

The measurement of loyalty is a topic of great interest for the marketing academic literature. The relation that loyalty has with the results of organizations has been tested by numerous studies and the search to retain profitable customers has become a maxim in firm management. Tourist destinations have not remained oblivious to this trend. However, the difficulty involved in measuring the loyalty of a tourist destination is a brake on its adoption by those in charge of destination management. The usefulness of measuring loyalty lies in being able to apply strategies which enable improving it, but that also impact on the enhancement of the organization's results. The study of tourists’ loyalty to a destination is considered relevant for the literature and from the point of view of the management of the multiple actors involved in the tourist activity. Based on these considerations, this work proposes a synthetic indictor that allows the simple measurement of the tourist's loyalty. To do so, we used as a starting point Best's (2007) customer loyalty index adapted to the case of tourist destinations. We also employed a variable of results – the tourist's overnight stays in the destination – to create a typology of customers according to their levels of loyalty and the number of their overnight stays. The data were obtained from a survey carried out with 2373 tourists of the city of Seville. In accordance with the results attained, the proposal of the synthetic indicator to measure tourist loyalty is viable, as it is a question of a simple index constructed from easily obtainable data. Furthermore, four groups of tourists have been identified, according to their degree of loyalty and profitability, using the number of overnight stays of the tourists in their visit to the destination. The study's main contribution stems from the possibility of simply measuring loyalty and from establishing four profiles of tourists for which marketing strategies of differentiated relations can be put into practice and that contribute to the improvement of the destination's results.

Introduction

To understand what the tourist's loyalty depends on and how it is formed has become a maxim for managers of tourist firms and destinations. Loyalty is considered to be the best predictor of future behavior and a source of competitive advantage and success in the market (Gursoy, Chen, & Chi, 2014; Sun, Chi, & Xu, 2013). Therefore, a tourist destination, the same as any organization, must attract and retain its target market (Gursoy et al., 2014). Under this perspective, the comprehension of the elements which determine the loyalty toward a destination and the way in which they inter-relate to determine loyalty has become a fundamental matter. Numerous studies have tackled this question and have proposed elaborate models of structural relations (Forgas-Coll, Palau-Saumell, Sánchez-García, & Callarisa-Fiol, 2012; Prayag & Ryan, 2012; Zhang, Fu, Cai, & Lu, 2014) which show the role that expectations, image and perceived value (Faullant, Matzler, & Fuller, 2008; Um, Chon, & Ro, 2006), satisfaction (Bigné, Sánchez, & Sánchez, 2001; Chen & Tsai, 2007; Poria, Reichel, & Cohen, 2011; Wang, Wu, & Yuan, 2010; Yuksel, Yuksel, & Bilim, 2010) and perceived quality (Olorunniwo, Hsu, & Udo, 2006) have in the generation of loyalty toward the destination. The majority of these studies consider loyalty to be a bi-dimensional variable, made up of an attitudinal component and a behavioral component. Attitudinal loyalty, considered to be the most powerful source of loyalty, tends to indicate a favorable personal attitude toward the destination, and is based on the emotions caused in the tourist by this destination. This attitude strongly shows the inclination of the individual to recommend the destination to other tourists, even in situations in which they are not repeating their visits (Kursunluoglu, 2011).

Loyalty toward the destination is important due to the role that it plays in obtaining profitability (Yoo & Bai, 2013) and in its subsequent growth and development. This characteristic, common to firms and destinations, is even more relevant in the case of the latter. This is because of the effect that tourism has on economic growth, employment and the welfare of citizens, especially in economies strongly linked to the tourist sector. Therefore, the measurement of loyalty should be accompanied by the quantification of the effect of this loyalty toward the destination on some variable of profitability or growth. One of the indicators most used to establish the situation of destinations regarding the tourist is the number of overnight stays. This figure, exclusively relative to physical units of demand, is not a measure of profitability, but is considered to be a direct antecedent of it, as when it is higher, the incomes obtained by the destination are greater, due to the impact on lodging, transport, attractions, catering and business in general.

Based on these considerations, this work means to establish a synthetic indicator of tourist loyalty toward a destination which facilitates its measurement by the agents involved. This indicator, which we will call Tourist Loyalty Indicator (TLI), is going to include the main antecedents of loyalty gathered together in previous studies. Likewise, we mean to establish a typology of tourists, according to their loyalty and the number of their overnight stays in the destination. The four resulting groups are going to differ as to overnight stays and/or loyalty and, therefore, will need differentiated relational marketing strategies to maximize their future profitability. The value of this typology is unquestionable for those in charge of managing tourist destinations. They will in this way be able to aim their efforts more precisely for each group. This will undoubtedly increase the efficacy and efficiency of their marketing actions.

To achieve the aims proposed, we carried out an empirical study among tourists who were visiting the city of Seville. The destination chosen registered in 2016 more than 2.7 million people lodged in hotel establishments and apartments and a figure of overnight stays of 4.9 million. This makes it the most visited city in Andalusia and the third most visited urban destination in Spain, after Madrid and Barcelona (National Institute of Statistics – INE-2017.

Review of the literature

The tourist's loyalty toward the destination

Customer loyalty is a recurring topic in academic research. Since 1956, more than three thousand articles have been written on “customer loyalty” in journals with an impact factor in the area of social sciences, according to the results offered in the Web of Science (WOS). However, there are only ninety-five articles on “destination loyalty”, the first of them dating from 2001. Most of these studies try to find out the factors which antecede or explain the tourist's loyalty toward a destination (Bigné et al., 2001; Chen & Tsai, 2007; Faullant et al., 2008; Olorunniwo et al., 2006; Poria et al., 2011; Um, Chon, & Ro, 2006; Wang et al., 2010; Yuksel et al., 2010).

According to the literature, the benefits of loyalty are related with the current and future value of the benefits and with the organization's continuity (Moliner, Gil, & Ruíz, 2009). In this vein, the tourist's loyalty implies a stable source of incomes, as well as an improvement of the destination's benefits as customer retention means less costs than those required to attract new customers.

Most works define destination loyalty in relation to the intention to revisit and the intention to recommend (Chen & Gursoy, 2001; Chi & Qu, 2008; Chi, 2011; Oppermann, 2000; Pike, 2010; Prayag & Ryan, 2012; Yoon & Uysal, 2005). Loyalty is multidimensional, behavioral and attitudinal components having the greatest acceptation. From the first perspective, loyalty is reflected in repeat purchases, while attitudinal loyalty considers recommendations to friends and family. If both aspects are considered the construct is predicted better (Dimitriades, 2006) and a more exact representation of the tourist's loyalty is provided (Chen & Gursoy, 2001). When exclusively contemplating a tourist's behavior through repeated visits to a destination, this may not really reflect loyalty in the area which we are dealing with. When tourists travel with the motive of having a new experience, it is unlikely for them to repeat the visit to a destination, so destination loyalty may not involve repetition (Iso-Ahola, 1982).

Destination loyalty is a key element in marketing strategies in so far as it is the best predictor of post-visit behavior (Chen & Chen, 2010). This loyalty is achieved by surpassing the tourists’ expectations, providing unique experiences and assuming a commitment with these tourists. At the same time as valuing their opinions and reducing the effort to deal with the problems which arise during the relationship, they must be considered as unique customers (McGarry, 1995). The response of these tourists is seen in their favorable intention to revisit the destination and to give positive references about it in their close environment (Mohamad, Ali, & Ghani, 2011).

The intention to return to the destination is considered to be a key component of loyalty and many authors have gone thoroughly into this concept, trying to determine the factors which enable attaining high values in the probability of repetition (Backman & Crompton, 1991; Cronin, Brady, & Hult, 2000; Petrick, Morais, & Norman, 2001). In the field of tourism there are various works which have used this indicator as a measure of loyalty (Kim, Eves, & Scarles, 2009; Petrick, 2004; Qu, Kim, & Im, 2011).

The likelihood of recommending the destination to other people is considered these days as a clear indicator of loyalty. The intention to recommend refers to “the informal person-to-person communication between a perceived noncommercial communicator and a receiver regarding a brand, a product, an organization, or a service” (Harrison-Walker, 2001, p. 63). This intention to recommend the destination is of great relevance for its success as the high perceived risk in the decision of choosing the tourist destination brings about a strong need for qualified information and trust in the tourist. In this way, the references received from third parties are going to affect the choice of the destination (Kivela & Crotts, 2006; Nam, Kim, & Hwang, 2016; Qu et al., 2011; Tussyadiah, Park, & Fesenmaier, 2011).

Antecedent variables to loyalty

The literature has tackled the study of a broad set of antecedents to loyalty, among others: image, perceived quality, satisfaction (Bigné et al., 2001), the safety of the destination, cultural differences, previous experiences (Chen & Gursoy, 2001), the motive for traveling and satisfaction with the trip (Yoon & Uysal, 2005). Most of the previous research in this field points out that the tourist's satisfaction, the destination's image and the quality of service are predictors of loyalty. A recent study has shown that satisfaction, perceived value and the destination's image, among others, are antecedents to the destination loyalty of domestic tourists in China (Sun et al., 2013).

Expectations: expectations play a central role in the discussion of customer satisfaction and service quality. Parasuraman, Berry, and Zeithaml (1988) define expectations as predictions made by consumers about what is likely to occur during an imminent transaction, or as beliefs about attributes which firms in general should have. Numerous studies centered on the tourist sector have found a direct relation between the customer's expectations and satisfaction (Oliver & Burke, 1999; Omachonu, Johnson, & Onyeaso, 2008; Voss, Parasuraman, & Grewal, 1998), and between this and loyalty (Prayag, Hosany, & Odeh, 2013). Although there are no studies which directly relate expectation with loyalty, it can be considered that the latter will be affected, at least indirectly, by the tourist's expectations regarding the destination.

Service quality: In the broad sense, service quality is “a global judgment, or attitude, relating to the superiority of the service” (Parasuraman, Zeithaml, & Berry, 1988, p. 16). In tourism, many works analyze the role of service quality in forming behavioral intentions (Baker & Crompton, 2000). Service quality has been related with satisfaction (Chi & Qu, 2008; Fornell, Johnson, Anderson, Cha, & Bryant, 1996; Mason & Nassivera, 2013; Petrick, 2004), at the same time as being a variable which favors word-to-mouth comments and contributes to the repetition of the visit (Cole & Illum, 2006).

Tourist service quality involves the valuing of the aspects which are under the control of the supplier, inasmuch as from a global perspective, the quality of the tourist experience is associated with psychological benefits and affective satisfaction (Cole & Crompton, 2003). In the tourist sector, there are many studies which find a positive relation between perceived quality and satisfaction with the accommodation (Alexandris, Dimitriadis, & Markata, 2002; Clemes, Gan, & Ren, 2011; Ingram & Daskalakis, 1999).

Satisfaction: Satisfaction is one of the most important concepts in the marketing literature due to it being a fundamental element for the survival of any business (Anderson & Sullivan 1993; Chiou, Droge, & Hanvanich, 2002; Kozak, 2001; Sun et al., 2013; Zeithaml, Berry, & Parasuraman, 1996). Diverse works in the area of tourism have dealt with the study of the tourist's satisfaction (Song, Veen, Li, & Chen, 2012; Sun et al., 2013). According to these works, satisfaction is a requirement for the success of a tourist destination due to this satisfaction being one of the most important predictors of a tourist's loyalty (Ozdemir, Aksu, Ehtiyar, Cizel, Cizel, & Icigen, 2012). The tourist's global satisfaction is considered to be the most important antecedent of tourist destination loyalty (Chi & Qu, 2008; Chi, 2012; Mohamad, Ali & Ghani, 2011; Neal & Gursoy, 2008).

In the tourist area, satisfaction comes from tourists comparing their expectations with the results of the experience of the trip, the experience surpassing the expectations (Kim & Perdue, 2011).

The consequences of satisfaction with a tourist experience are basically an increase in the intention to return to the destination as well as recommending it to third parties (Back & Parks, 2003; Back, 2005; Chi & Qu, 2008; Chi, 2012; Clemes et al., 2011; Kozak & Rimmington, 2000; Kozak, 2001; Petrick et al., 2001; Prayag & Ryan, 2012; Yoon & Uysal, 2005). Both the repetition of the visit and the recommendation are considered two key indicators of customer loyalty, a consequence of the tourist's satisfaction (Prayag, Hosany, & Odeh, 2013). Satisfaction has also been related with the tourist's perception of a destination's quality and image (Chi, 2012; Song et al., 2012).

Destination image: Image management is one of the most important responsibilities of any destination due to the visitors’ image of a destination having a strong impact on their evaluation and the behavior of selecting a destination (Chi, 2012; Nunkoo, Smith, & Ramkissoon, 2013; Sun et al., 2013). Through promoting a tourist destination it is meant to project an image which makes this destination attractive and desirable for potential tourists (Beerly & Martín, 2004).

One of the first definitions suggests that the destination image can be defined as the expression of all the knowledge, impressions, prejudices and emotional beliefs that an individual or group has concerning a specific place or object (Lawson & Baud-Bovy, 1977). Many conceptualizations of the concept of destination image have been contributed over time based on the research approaches used. Nevertheless, three inter-related components can be identified (Martín, Beerli, & Nazareno, 2016): 1) perceptual/cognitive, related to tourists’ beliefs about a destination's attributes; 2) affective, related to the emotional response of the tourists about the destination; and 3) global, which refers to the global impressions that the tourist has of the destination. The destination image can be defined as “the perceptions about the place as reflected by the associations held in tourist memory” (Cai, 2002, p.723). In the same line, Assaker, Vinzi, and O’Connor (2011) affirmed that they consider the destination image to be a holistic perception.

The destination image influences the tourists’ future intentions, be it their intention to revisit the destination or recommend it (Bigné et al., 2001; Chen & Tsai, 2007; Mahasuweerachai & Qu, 2011). It is therefore an antecedent of the tourist's destination loyalty (Ashworth & Goodall, 1988; Chen & Tsai, 2007; Cooper, Fletcher, Gilbert, & Wanhill, 1993; Lee, Lee, & Lee, 2005; Mansfeld, 1992), and a key element to consider in measuring this loyalty.

Loyalty indices

An index is a composite measure which summarizes various indicators or specific observations about the same phenomenon. Its design responds to the need to synthetically and simply express the variation in a set of values which in their primary form are difficult to understand. A loyalty index must therefore be a synthetic value, established in a scale, which enables the quantification of loyalty and that includes all the relative elements which determine it.

The majority of loyalty indices work on the perceptions which customers have about the topics included in surveys used to measure the observable variables, and tend to include three variables: global satisfaction, repurchase likelihood, and the probability of recommending the product to other people (Best, 2007; Geng-Qing & Qu, 2008). However, given the differential characteristics of destinations and fruit of the theoretical review carried out, we propose the following expression for the tourist loyalty index (TLI):

• TLI = EXPT × PQ × GID × TSI × IRECOM × IREP

• where

• TLI = tourist loyalty index

• EXPT = expectations

• PQ = perceived quality

• GID = global image of the destination

• TSI = tourist's satisfaction index

• IRECOM = intention to recommend

• IREP = intention to repeat the visit

Methodology

To respond to the research aims, we followed a two-phase procedure. The first was to calculate a TLI, based on the expression proposed in the previous section. The second was to obtain a matrix which enabled classifying the tourists according to the loyalty-overnight stays binomial. To do so, we carried out a personal survey, using specially trained interviewers, of tourists who were visiting the city of Seville, obtaining a total of 2373 valid questionnaires. The profile of the sample analyzed is shown in Table 1. The demographic profile of the sample analyzed is shown in Table 1. The sample is primarily made up of Spanish tourists (53.4% of the sample). Moreover, the highest percentage of respondents are women (61.5%) and young people - 81.5% of the sample are less than 44 years old. As to the level of studies, respondents who have had secondary education (47.2%) and university education (44.6%) stand out. Regarding travel-related habits, most of the respondent travel less than three times a year (39.3%). The most common means of transport is planes (50.4%) and the tourists especially opt for independent travel (56.1%).

Table 1.

Sample profile.

Criteria	Levels	%
Origin	Spain	53.4
	European Union	29.4
	Rest Europe	2.0
	Others	15.2
Gender	Men	38.5
	Women	61.5
Age	Under 26	36.5
	26–44	45.0
	45–64	17.4
	65–	1.1
Level of studies	Without education	2.4
	Primary studies	5.8
	Secondary studies	47.2
	University studies	44.6
Annual frequency of trips	Less than three	39.3
	Three	36.9
	More than three	23.8
Means of transport	Plane	50.4
	Car	17.2
	Others	32.4
Way of organizing the trip	Totally organized	31.6
	Partially organized	12.2
	Independent	56.1
Number of times have been in Seville	First time	47.9
	Second time	26.2
	Third time	9.9
	More than three times	16

The study's first aim is to obtain a synthetic indicator which allows the measuring of the tourist's destination. To do so, the measurement instruments for each of the concepts which have been included in the TLI have been quantified through a unique item. This item will gather together the global impression that the tourist has about each of the variables included: expectations, service quality, satisfaction, destination image, intention to revisit, and intention to recommend the destination. To respond to the second aim, we included a question related to the nights that the tourists had spent or were going to spend in the destination. Table 2 shows the indicators used.

Table 2.

Measurement indicators.

Measurement indicators
Expectations (EXP)	In general, what were your expectations regarding the service quality which you expected to receive in Seville? 5: very high; 1: very low
Perceived quality (PQ)	In general, how would you evaluate the service quality received during your stay in Seville? 5: very high; 1: very low
Global image (GID)	In general, and taking into account the experience of this visit, the image that you have of Seville is: 5: very positive; 1: very negative
Satisfaction (TSI)	Qualify your level of global satisfaction regarding your visit to Seville 5: very satisfactory; 1: not at all satisfactory
Intention to recommend (IRECOM)	Will you recommend those close to you to visit Seville? 5: certainly; 1: never
Intention to repeat visit (IREP)	Are you thinking of visiting Seville again? 1: never; 5: for sure
Overnight stays	Number of nights you have spent or will spend in your visit to Seville

Results

Tourist loyalty indicator

The indices of loyalty are quantified on a scale between zero (minimum value) and a hundred (maximum value). In them, the customer satisfaction index (CSI) tends to be expressed based on 100, the rest of the variables referring to a unit basis. Following this model, all the variables were appropriately recoded, in such a way that the value five of the initial scale became the value one on the final scale (a hundred in the case of the satisfaction variable) and the value one of the initial scale was recoded to the value zero of the final scale. Having recoded all the variables, the tourist loyalty index (TLI) was calculated applying the expression proposed (TLI = EXPT * PQ * GID * TSI * IRECOM * IREP). Table 3 shows the descriptive statistics for the TLI and its components, considering the number of valid questionnaires, the average value of each of the indicators, the mode, and also the minimum and maximum values that the indicators attain.

Table 3.

TLI descriptive statistics.

		GID	EXPT	PQ	IRECOM	IREP	TSI	TLI
N	Valid	2373	2373	2373	2373	2373	2373	2373
	Lost	0	0	0	0	0	0	0
Average		0.94	0.9	0.92	0.94	0.89	94	71
Mode		1	1	1	1	1	100	100
Minimum		0.5	0.5	0.5	0	0	50	0
Maximum		1	1	1	1	1	100	100

Loyalty-overnight stays matrix

The loyalty-overnight stays matrix is an adaptation for our study of the matrix proposed by Best (2007) to manage customer loyalty and profitability. This instrument enables the classifying of the customers of any organization into four types, according to their loyalty and profitability, using the averages of both variables as cut-off values. In this case, we have used as a variable that summarizes loyalty the TLI calculated in the previous phase and as a variable summarizing profitability the number of overnight stays of the tourists in their visit to the destination. Table 4 shows the results obtained and the descriptive profile of the tourists which are included in each group.

Table 4.

Loyalty-overnight stays matrix. Sociodemographic profile.

3.06 nights	High potential tourists	High performance tourists
	43% under 25 years old. 31% 26–44 years old	44% under 25 years old. 38% 26–44 years old
	66% have university studies	58% have university studies
	44% are from EU and 36% from Spain	31% are from EU and 48% from Spain
	67% have a partner	66% have a partner
	5.6 nights	6 nights
	TLI = 33	TLI = 93.4
	Unprofitable tourists	Underutilized tourists
	37% under 25 years old. 49% 26–44 years old	32% under 25 years old. 48% 26–44 years old
	52% have secondary studies	53% have secondary studies
	30% are from EU and 58% from Spain	25% are from EU and 57% from Spain
	58% have a partner	58% have a partner
	1.6 nights	1.6 nights
	TLI = 28.6	TLI = 94.5
	TLI = 71.58

Based on both variables, TLI and overnight stays, and setting out from the loyalty-profitability matrix (Best, 2007), we establish the following categories of tourists:

• •

  Unprofitable tourists: these are the ones who spend less nights in the destination than the sample's average value and who also show a loyalty below the average. Normally, they are new to the destination and the majority do not have the intention of returning. They are 24.7% of the sample analyzed and have an average TLI of 28.60 and an average number of overnight stays of 1.6 nights. Referring to their sociodemographic profile, we note that most are from Spain, are between 26 and 44 years old and have secondary school studies. Regarding the characteristics related with their behavior when traveling, we point out that only 13% travel more than three times per year, that 41% are on their first visit to Seville, that they came by plane (42%) or by car (41%), and that 54% organized their own trip, without using an agency or intermediary. Lastly, and related to the TLI (Table 5), these are the tourists who have the least probabilities of repeating their visit and of recommending the destination to their close relatives. We also note reduced values in the indicators of global image, of expectations, and of perceived quality. All this is reflected in the level of satisfaction with the destination, the least of the four groups of tourists analyzed.

  Table 5.

  TLI structure.

  	Unprofitable	High potential	High performance	Underutilized
  GID	0.881	0.822	0.975	0.985
  EXPT	0.787	0.666	0.987	0.980
  PQ	0.791	0.843	0.992	0.988
  TSI	85	88.6	97.8	99
  IRECOM	0.791	0.942	1	1
  IREP	0.652	0.852	1	1
  TLI	28.6	33	93.4	94.5
• •

  Underutilized tourists: these tourists are 47.9% of the sample and are characterized as having a higher than average loyalty (TLI = 94.50) and a figure of overnight stays below the average (1.6 nights). Their sociodemographic profile shows that they are between 26 and 44 years old, have had secondary education and reside in Spain. Concerning how they travel, 21.1% do so more than three times per year, 44% are visiting Seville for the first time, and have come by plane (50%) or by car (30%), and 48% have organized their own trip, without the intervention of an agency or intermediary. In these aspects, they are differentiated from the unprofitable tourists, as they travel more, tend to use planes more and have more trust in agencies and other intermediaries to plan their trip. If we analyze the TLI structure for this group of tourists, we note that they are the most loyal of the sample, having maximum values in recommendation and repetition. The indicators for global image, satisfaction, expectations and perceived quality are also very high, which means that we have a group of people who will be intrinsically loyal to the destination and who will probably repeat the experience in the future, if they have options which interest them.

• •

  High potential tourists: this is a group which stays more than five nights in the city but has scant destination loyalty (TLI = 33). They are 16.9% of the sample analyzed and are characterized by their youth (the under 26 predominate), though it is the group with the greatest percentage of people over 44 years old (25%). It is also the segment with the greatest proportion of university studies – 66.3% – and they are tourists who come mainly from countries belonging to the European Union (43.8%). Their behavior when traveling indicates a greater frequency than the rest of the groups analyzed as 39.7% travel more than three times a year. The percentage visiting Seville for the first time is also significant (60.2%), as is their tendency to organize their own trip without intermediaries – 81% do so in this way. The TLI data indicate a poor valuation of the destination image in comparison with the other groups of tourists and they are also the ones who have a more reduced service expectation.

• •

  High performance tourists: the last group of tourists is characterized by an above average TLI (93.4) and a number of overnight stays which doubles the sample's average (6). They are 16.9% of the total of tourists and their sociodemographic profile indicates that they are from Spain (48%) or the European Union (31%), although this is the group with the greatest percentage of tourists from other continents (20% of the total). They are mostly under 44 years old and the majority of them have university studies. The tourist profile shows that 37% travel more than three times a year, that they mostly use planes (64%) and that they are very independent when organizing their trip (66% do not use intermediaries). Lastly, the TLI study shows that they are tourists with the greatest expectations and perceived service quality, have a high intention of recommendation and of visiting the destination again. The indicators which reflect more reduced values for this group are the global image and satisfaction.

Table 5 synthetically gathers the average values of each of the indicators which make up the TLI index, based on the four groups identified, in such a way that the differences between them can be noted.

Discussion and conclusions

Taking into account the growing importance of the study of loyalty in the tourist area, this work proposes a loyalty index applied to a tourist destination. This study contributes a simple and practical measurement of a tourist's degree of loyalty to a tourist destination. Those in charge of the planning and managing of a tourist destination can easily identify the factors which enable a destination's degree of loyalty to be increased, so they can adopt the appropriate measures which allow the strengthening of this loyalty. The tourists who have a greater expectation related to service quality, who perceive a high level of service quality, who have a positive image of the destination, who show themselves to be satisfied with the tourist experience, who recommend the destination to third parties and who have the intention of repeating their visit are very loyal visitors. If, as well as loyal, these tourists have more overnight stays than the average, we have high performance tourists for whom the development of personalized marketing strategies is recommendable.

A profile of the visitors can be identified according to the overnight stays. The unprofitable and underutilized tourists have in common less overnight stays in the destination than the average, in this specific case identical (1.6 nights). And they are similar as to their sociodemographic characteristics, both regarding where they are from and their age and level of studies.

Exactly the same takes place with the tourists who have a higher number of overnight stays, the so-called high potential and high performance tourists. All of them have overnight stays in the destination of around 6 nights and share a similar profile of age, origin and education. In these aspects, they are differentiated from the previous groups by having university studies and being mainly from other countries of the European Union.

Implications for management

This work has two main managerial implications. Firstly, the indicator proposed can help the agents involved in the management of tourist destinations to quantify the loyalty of visitors very easily. The measurement of the loyalty of tourists is a fundamental step to design and implement practices of improving loyalty. To foster tourist loyalty it is necessary for the agents involved to act on each of the components of the TLI; that is, on the expectations of the tourists, the level of perceived service quality, the destination's global image, the visitor's satisfaction, and also their intention to recommend the destination and repeat their visit.

On the other hand, the segmentation of the visitors according to their level of loyalty and profitability enables the development of specific strategies of relational marketing with the customers (Best, 2007). Personalized programs can be recommended for the high performance tourists, so that stable long-term relations are established based on contributing a greater value to the tourists in order to foster their satisfaction. These are special customers with whom it is necessary to develop relations at an individual level. For the high potential tourists, strategies would have to be designed which allow constructing loyalty-based relations; they are visitors prone to be easily lost. The underutilized tourists, although they are very loyal to the destination have a low profitability. In this case, communication tools can develop a fundamental role with the aim of increasing the number of these visitors’ overnight stays. Finally, with the unprofitable tourists it is recommended to go somewhat deeper into an analysis of them with a view to knowing if, through the appropriate strategies, it is possible to transform them into loyal and profitable tourists. In any case, great marketing efforts should not be made with this segment.

Theoretical implications

From a theoretical perspective, this work is relevant as it proposes a specific index to measure the loyalty of tourists. The index proposed is of great usefulness for the agents involved in the planning and management of destinations. Thus, we have estimated loyalty in a novel manner, contemplating all those determinant factors which, according to the literature, influence the visitor's loyalty. The index proposed is characterized by its operational simplicity, as each of the indicators which intervene can be measured easily and quickly. In the very competitive context in which any tourist destination is developed these days, to attain the visitors’ loyalty confers a competitive advantage and, therefore, works which go thoroughly into this idea must be considered valuable.

Moreover, the study offers a typology of tourists based on their loyalty and number of overnight stays. The identification of this group of tourists is considered indispensable for the development of different marketing strategies which foster destination loyalty, at the same time as contributing to increasing the profitability generated by these tourists.

Limitations and future research lines

One of this work's limitations is the design of the very TLI proposed. In this indicator, all the components have the same relative weight. Nonetheless, it would be necessary to go deeper into its analysis with a view to identifying if all the variables have the same relative importance in the indicator, or if it is necessary to introduce coefficients which enable differentiating the importance of each of the aspects contemplated.

Likewise, it would be desirable to use other indicators apart from profitability; in particular, those directly related with the incomes generated by the tourists in the destinations.

Future works could include more characteristics of the tourists, such as their personality, their degree of familiarity with the destination, their motives for visiting the destination, and so forth, with the aim of analyzing the possible differences in the degree of loyalty of the tourists based on these variables. Furthermore, in this work loyalty is investigated in the context of an urban destination. Its appropriateness could be studied in the framework of other, different destinations.