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Article

The Internal Demand of Cultural Tourism: Understanding Satisfaction and Fidelity to Destination in Spain through a Non-Linear Structural Model

by
María-Dolores Sánchez-Sánchez
1,*,
Carmen De Pablos-Heredero
2 and
José-Luis Montes-Botella
1
1
Department of Applied Economy, Rey Juan Carlos University, 28032 Madrid, Spain
2
Department of Business Organization, Rey Juan Carlos University, 28032 Madrid, Spain
*
Author to whom correspondence should be addressed.
Sustainability 2021, 13(23), 13487; https://doi.org/10.3390/su132313487
Submission received: 9 October 2021 / Revised: 23 November 2021 / Accepted: 26 November 2021 / Published: 6 December 2021
(This article belongs to the Special Issue Management of Cultural and Heritage Tourism and Its Sustainability)
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Abstract

:
The new habits of tourist consumption favor the rise of cultural tourism, either as the primary or complementary offer of a destination. Therefore, it is necessary to deepen the study of the behavior of cultural tourism demand. This research aims to develop a structural model that allows measuring the main variables that affect the satisfaction and loyalty of the internal demand of the cultural tourist to a heritage destination. The results are helpful for the design of tourism management. The hypotheses posited have been tested using non-linear structural equations (SEM), estimated with data from the National Statistics Institute on internal demand for cultural tourism in Spain (n = 18,024). The results confirm the importance of socio-cultural variables and the tourist’s experience on fidelity to the visited destination. Furthermore, the negative relationship between the repetition of the visit and satisfaction is striking.

1. Introduction

In the current economic context, the success of tourist destinations depends both on their ability to attract travelers and the loyalty of tourists [1,2]. Therefore, the study of tourist demand and its behavior is a priority in carrying out marketing strategies focused on the different demand segments and in developing specific promotional and marketing policies [3].
Finding competitive advantages that allow emerging destinations to attract the tourist flow or maintenance in mature destinations is essential in order to position a tourist destination [4]. In both cases, knowing the visitor’s loyalty and satisfaction as a background to their future behavior are essential to differentiate themselves within the tourist offer. For this, it is necessary to understand how tourist behavior affects loyalty to the destination, as the tourist influx to destinations results from tourists’ behavior [5].
In addition, the current volatility of the world economy, generated by the COVID-19 pandemic and the possible perception of health insecurity in specific destinations, may lead to a temporary decrease in the international tourist flow [6]. Besides, heritage is subjected to restrictions tTo make cultural destinations more sustainable [7,8]. Both circumstances can also be an opportunity to build loyalty in domestic tourism demand.
Previous economic crises reveal that, in these situations, the trend to make short-stay trips to destinations close to the place of residence increases [9]. In addition, the COVID-19 pandemic has modified the behavior of tourists, who now prefer national destinations with less tourist flow [10].
Therefore, it is necessary to deepen the study of the behavior of domestic tourism demand, due to its strong relationship with the economic growth of a country [11], especially the segments of domestic demand with high purchasing power, such as the cultural tourist [12].
The study aims to provide greater knowledge about the loyalty of the internal demand of a cultural tourist to the destinations he visits. By establishing what factors influence the increase in the value perceived by the cultural tourist in the destination, it will be possible to understand and explain their satisfaction and future behavioral intentions (their loyalty). Furthermore, a statistical model was proposed, estimated, and verified to understand its behavior better.
Therefore, this work focuses on identifying and quantifying the variables that can explain the experience of consumption of cultural tourism, the relationships between them, and their influence on fidelity to the destination. In addition, the value related to the use or experience of tourism consumption is analyzed [2,13,14], along with fidelity to the object of consumption, i.e., the destination.
Spain has been chosen as the case for the study because it is a tourist power. In 2019 it received 83.7 million foreign visitors. It is worth highlighting the strategic importance of the tourism sector for its economy, which, before the COVID-19 pandemic, represented 12.5% of its GDP [15]. In addition, Spain could further diversify its tourism model towards other types of products, such as cultural tourism derived from its rich heritage. Proof of this is that UNESCO has recognized 15 historic centers in Spain as World Heritage cities.
An empirical analysis was carried out based on the data on culturally motivated tourism demand provided by the Resident Tourism Survey. This survey is carried out periodically by the National Statistics Institute (NSI), to provide detailed information on the number of trips, the traveler’s profile, and the motivation of resident households in Spain [16].
From the theoretical frameworks that explain the variables that would make up the customer experience [17,18], the Resident Tourism Survey questionnaire, which is considered to influence the fidelity of the cultural tourist, was chosen.
Subsequently, the 15 hypotheses that make up the theoretical model have been posited and validated by non-linear structural equation models (SEM). After presenting the results, the discussion, the conclusions, theoretical and practical contributions, recommendations, and future lines of research are explained.
The knowledge generated by this study constitutes a necessary step to provide information to the agents involved in tourism management to improve their decision-making processes.
More efficient relationship marketing strategies to achieve a more significant competitive advantage and become the desired tourist destination through tourism strategies in the short and long term can be put into action to achieve a more significant competitive advantage and become the desired tourist destination through tourism strategies in the short and long term. It also helps to understand how the development of tourism management policies that generate social and economic profitability in the destination can be considered [19].

2. Conceptual Framework

2.1. Components of Fidelity to Destiny

The tourism sector has investigated consumer loyalty to destinations in recent decades, as it is key to their commercial positioning. In addition, the repetition of the visit, or its recommendation to third parties, has been analyzed. This last aspect is of great importance, as it is one of the sources of information that highly influences potential tourists [20,21].
In leisure and tourism services, the study of tourist loyalty derives from the concept of customer loyalty, applying the product category composed of services and products to the tourist destination [22,23]. Because of this approach, tourist loyalty uses the same variables for its measurement as those used to measure customer loyalty from a behavioral, attitudinal, or composite perspective. Therefore, the definition of the tourist fidelity construct is comprehensive, and, in the scientific literature, there is no single way to analyze it [24].
The measurement of tourist loyalty adopts a factor composed of two dimensions [25,26,27,28]. The first is behavioral loyalty, evaluating the degree of loyalty for the service’s repurchase or repetition of the visit [29]. The second is attitudinal loyalty, as a favorable attitude towards the product or tourist destination. This is measured by positive recommendations—word of mouth communication—to third parties [30].
The result of the two previous approaches is the conative or compound conceptual framework, which analyzes fidelity as a two-dimensional construct made up of the attitudinal and the behavioral [31]. Thus, fidelity is measured not only by its antecedents or consequences, but also by disposition, emotion, and action, highlighting dimensions of tourist fidelity, such as the feeling of attachment or commitment to a destination [32,33].
Tourist loyalty will result from jointly integrating the variables present in both dimensions [22,34] to provide a complete vision of tourist loyalty to the destination [35]. Therefore, the tourist’s loyalty to a destination is expressed through a positive attitude towards a place. It is later specified in behavior that implies the repetition of the visit, its recommendation, or both.

2.2. Behavioral Dimension of Fidelity to Destiny

The loyalty to the destination of the cultural tourist, in this study, is analyzed from the behavioral point of view, measured by repeating the visit in the 16, 400 interviews used. This is the indicator used in the Resident Tourism survey to analyze visitor loyalty to the destination, considering the data collected from the respondents on whether their stay in the destination is for the first time.
A single item is used to explore this construct. Large samples can provide reliable information to measure fidelity without making the questionnaire too long [36].
Studies on tourist behavior use repeat visits to analyze visitor loyalty to the destination [37]. The use of this indicator derives from the evidence that the repeated acquisition of a brand increases the possibility of it being bought again the next time [38]. Thus, tourists can carry out a repeated consumption of the destination as a product by repeating the visit, which increases the possibility of a future return of the visitor to the destination. Hence, the degree of tourists’ loyalty to a destination is reflected in their intentions to revisit it [36].
Numerous tourism investigations have focused on behavior based on analyzing the different factors that influence the repetition of the visit to a destination [33,39]. (In this sense, some authors discriminate tourist behavior by segmenting the demand among those who have been to the destination before, and those who have gone for their first time [40,41].

2.3. Variables That Influence Tourist Loyalty

Next, the conceptual foundations of the different factors that influence the fidelity of the cultural tourist are reviewed, focusing on the variables present in the resident survey explored on the proposed model.
Various factors can influence the tourist’s behavior regarding their repetition of the visit, derived from the different attributes of the consumer or the tourist’s own experience (such as organizing the trip, activities carried out, or spending).
The characteristics of the destination condition the tourist experience. Whether emerging or mature, this defines a location’s tourism potential. The capacity of the destination to provide visitors with an experience in accordance with their expectations and needs will generate a higher or lower level of loyalty of the tourist towards the destination, manifested both in the intention of recommending it and of repeating the visit [25]. Furthermore, the quality of the tourist experience influences fidelity to the destination [42].
There is a tendency to repeat the visit when the tourist feels satisfied with the attributes of the destination during his first visit [41]. Boo, Busser and Baloglu [43], link the attributes of a product in marketing related to the perceived value, transferring them to the attributes of a destination. Its perceived value is a fundamental criterion in loyalty to the destination.
For this reason, the possibilities of the destination to carry out activities and the cultural tourist offer available are important elements in the loyalty of the tourist. If the possibilities of new activities have ended, it may be that, although the tourist experience has been positive, the visit will not be repeated.
However, if the tourist appreciates that he can live new experiences in the next visit or again enjoy performing the same activities that are attractive to him, he can revisit the destination [44].
Regarding the expenditure made before and during the trip, the tourist expenditure is determined by different factors, such as the psychographic aspects of the tourist (personality, lifestyle, interests, hobbies, and values), their primary motivation for traveling, or the characteristics of the trip [45,46].
The influence of spending and repeat visits to the destination has been analyzed concerning the number of visits made to the destination and the different spending patterns. The repetition of the visit can imply more or fewer expenses when looking for different experiences in each visit [47].
The socio-cultural profile of the cultural tourist would also have a direct impact on level of expenditure. His cultural level makes him an “active” tourist, eager to interact with the destination (heritage, local population etc.). In the case of the cultural tourist, the purchasing power is medium-high [48], making up a consumer willing to contract certain quality tourist services.
Within the tourist’s experience and behavior in the destination, the degree of organization of the trip is also important. The data provided by the survey object of this study on the organization of the trip reveals that the cultural tourist makes little use of standard organized trips (tourist packages). As it is a survey of the internal demand for cultural tourism, the lower use of tourist packages and the more significant presence of the independent travel organization are reflected. This is also explained by the fact that the contracting of this tourist product increases as the physical and cultural distance between the point of origin and destination increases [49]. Therefore, the preceding would impact not only the distribution of tourist spending at the destination, but also the experience of “living” in the destination visited.
The composition of the group of the trip also influences the repetition of the visit. For example, Ref. [50] analyze the typology of travel groups on Mallorca Island. Families have a greater intention of returning to the destination than groups of friends, who perceived a much more negative image of the destination.
Other factors that influence tourist loyalty may derive from the different attributes of the tourist. Thus, the socio-economic, demographic profile or personality would influence the degree of consumer loyalty [51]. In addition, the urban or rural place of residence, age and gender would be some of the variables that modulate their level of loyalty [38,52].
Correia, Zins and Silva [53] link older tourists with a greater possibility of repeating the visit than younger ones. Furthermore, the intention of the tourist to revisit the destination decreases as his purchasing power increases. In addition, [36] establishes a close relationship between socio-economic, demographic, and psychographic variables and their fidelity to the destination.
The relationship between satisfaction and loyalty has been approached by the marketing of services profusely, establishing satisfaction as an antecedent of the future intentions of customer behavior [54]. Satisfaction, or its absence, entails effects on customer behavior that can be manifested in the recommendation of the product to third parties, repurchase intentions, or complaints [30]. Therefore, buyer satisfaction has been analyzed as a predictor variable in creating customer loyalty towards a product or service.
However, this relationship is not always symmetric. Other studies consider that satisfied customers can be loyal to a product and not to a brand, increasing the opportunity to consume competitive products. Thus, satisfaction is also influenced by other mediating variables between both factors, such as trust or commitment between the company and the client [55]. Satisfaction does not always turn into loyalty.
In addition, it should be borne in mind that, in the tourism sector, we find ourselves with the need to have tangible and intangible elements that affect satisfaction. Among the former, the destination’s tourist resources, tourist infrastructure, accessibility, etc. Among intangibles, emotions lived, the quality of services perceived, and the degree of fulfillment of expectations are factors difficult to quantify, but they can impact to a higher extent in the tangible elements of tourist satisfaction [56].
Thus, the final satisfaction of the tourist is influenced by different variables such as, among others, those related to the socioeconomic profile of the visitor, his main motivation to travel [23] or the intrinsic characteristics of the destiny itself [42].
In the tourism literature, the role of satisfaction as an antecedent of the future behavior of the tourist consumer has been linked to the repetitiveness of the visit, and the recommendation of the destination.
The satisfaction research has been analyzed both as a precedent of fidelity to the destination [4,26] and as a predictor of the future behavior of the tourist, reflected in the intention of repeating the visit [42,57] and recommendation to third parties [36,58].
Regarding the repetition of the visit, the tendency to revisit a destination is demonstrated if the tourist has felt satisfied with the place’s attributes during his first stay [41]. Boo, Busser and Baloglu [43] transfer the marketing concept of the perceived value of the attributes of a product, to the perceived value of the attributes of a place, as a fundamental criterion in loyalty to the destination [59]. Along the same lines, several empirical studies have analyzed the causal relationships between satisfaction and loyalty with structural equations [23,26,60].
Likewise, research carried out on cultural destinations, such as the city of Seville (Spain) [61,62] or Eureka Springs in Arkansas, United States [26] demonstrate the relationship between the perceived value of the destination, its authenticity, general satisfaction, and its direct impact on fidelity to the destination.
The destination’s ability to provide the visitor with an experience in accordance with her expectations and needs has also been analyzed. A higher or lower level of loyalty expressed through the intention of recommending the destination or repeating the visit makes one more likely to revisit tourist destinations [25,42].
Therefore, general satisfaction is closely related to the positioning and competitiveness of tourist destinations within the tourist offer. It increases the flow of visitors [33,56,63,64].
However, there are also divergences regarding satisfaction as an influencing factor in tourist loyalty to the destination. As mentioned, the marketing of services has shown that customer satisfaction is necessary, though not sufficient, for their loyalty to occur. This highlights its non-linear nature. It does not always explain the relation between satisfaction and future intentions of consumer behavior, such as repeat visits.
However, to our knowledge, no study presents a global description of the different variables involved, addressing those mentioned earlier as only partial aspects. Thus, although there are studies that also try to quantify the relationships postulated in them, the present one extends the above in two aspects. On the one hand, it simultaneously considers a more significant number of variables, which allows a better understanding of the behavior of the cultural tourist. On the other hand, it tries to establish and quantify the possible relationship between them, highlighting their behavior at different levels and verifying that the relationships between them are not linear in nature, as assumed in previous studies.
Consequently, following the previous literature review, the following hypotheses are formulated:
Hypothesis 1 (H1).
The socio-economic profile of the tourist influences the general satisfaction.
Hypothesis 2 (H2).
The organization of the trip influences the general satisfaction.
Hypothesis 3 (H3).
The activities carried out at the destination influence overall satisfaction.
Hypothesis 4 (H4).
Spending before and during the trip influences overall satisfaction.
Hypothesis 5 (H5).
The organization of the trip influences the expenditure made before and during the trip.
Hypothesis 6 (H6).
The organization of the trip influences the activities carried out at the destination.
Hypothesis 7 (H7).
The expense made before and during the trip influences the activities carried out.
Hypothesis 8 (H8).
The socio-economic profile of the tourist influences the activities carried out in the destination.
Hypothesis 9 (H9).
The socio-economic profile of the tourist influences the degree of organization of the trip.
Hypothesis 10 (H10).
The socio-economic profile of the tourist influences the expenditure made before and during the trip.
Hypothesis 11 (H11).
The general satisfaction of the tourist influences the loyalty of the cultural tourist to the destination.
Hypothesis 12 (H12).
The organization of the trip influences the loyalty of the cultural tourist to the destination.
Hypothesis 13 (H13).
The Sociodemographic profile of the tourist influence fidelity to the destination.
Hypothesis 14 (H14).
The activities carried out at the destination influence fidelity to the destination.
Hypothesis 15 (H15).
The expense made before and during the trip influences the fidelity to the destination.

3. Proposed Conceptual Model

The model has been estimated. The hypotheses have been empirically tested with the data provided by the Resident Tourism Survey, which was carried out by the NSI, to study tourist trips and excursions done by the resident population in the primary family dwellings in Spain. This database offers detailed information on the number of trips and the profile of the traveler, and his motivation [65]. Those data whose primary motivation for the journey is culture are used. Only data that include the variable from Spain as a destination was used. The analyzed period spans from February to September 2018. Table 1 shows a summary of its main characteristics. The sample size is n = 18,024 (Table 2).
Based on the theoretical foundations exposed in the literature, the proposed conceptual model has been structured, identifying the most significant elements and proposing the interdependency system that relates them.
First, built on the literature review on the subject, those variables of the questionnaire of the Resident Tourism Survey that are considered to influence the behavior of cultural tourists in cultural destinations have been identified.
Next, the six model factors (constructs) are presented: the socio-economic profile, trip organization, activities carried out at the destination, spending, satisfaction, and loyalty. They all determine the behavioral model whose structure is to be tested through the relationships established in the proposed causal model. Finally, the six factors of the model are integrated and measured by different indicators.
The socio-cultural profile factor comprises nine indicators (age, sex, educational level, professional situation, economic activity, household income, characteristics of the municipality of residence, and the number of members that make up the household), 25 indicators make up the travel organization factor. Grouped by destination, type of trip (typology and composition), services used, and reservations made.
The factor activities carried out in the destination is composed of six indicators (cultural visits, attendance at cultural shows, other cultural activities, visiting cities, visiting rural destinations, and gastronomic activities). Fifteen indicators make up the factor of expenses before and during the trip, differentiating between expense and amount incurred. Finally, general satisfaction is made up of a single indicator, as well as the loyalty factor. Thus, a total of 57 indicator variables are included in the model.
According to the proposed conceptual model, the six factors composed of the socio-economic profile, trip organization, activities carried out at the destination, spending, satisfaction, and loyalty would be related to each other (Figure 1). The four factors referring to the profile, the organization, activities, and spending would directly affect the tourist’s general satisfaction, together with the other four latent variables, on the fidelity to the destination and the type of destination.

4. Methodology

The research framework used aims to estimate the causal relationships between the following six latent factors: the tourist’s socio-economic and cultural profile, the organization of the trip, the activities carried out at the destination, the expenses incurred, satisfaction, and fidelity to the destination or type of destination, estimated using a non-linear model of structural equations (SEM, structural equations modeling).
The exploratory nature of this research, as it is beneficial for analyzing relationships between latent variables (theoretical concepts) and indicators (empirical concepts) related through hypotheses in prediction-oriented research [66] justifies the SEM analysis. Therefore, it is a very effective tool to respond to empirical research purposes, the discovery of causal relationships between concepts, in social sciences, where it is necessary to use indicators to establish relationships [67,68].
In tourism, various empirical studies have been carried out, using structural equations, to establish causal relationships between various empirical factors, analyzing causal relationships with fidelity [56,60]. To our knowledge, all the models published to date are linear and, therefore, unable to capture the actual behavior of the relationship between the variables: “The truth is never linear”, or almost never [69].
The estimation of the model parameters was carried out using the statistical software WarpPLS 7.0 [70], which can estimate non-linear effects to test the full range of the relationships between the factors, which constitutes a closer approximation to reality. The value of these parameters was obtained by bootstrapping [71] with 100 samples of a size equal to the sample size n = 18,024.
The following criteria justify the use of WarpPLS 7.0: the modeling of the investigated problem is in an emerging state, the minimum requirements of the PLS regarding the sample size, the accuracy of the prediction, and comparatively low demands, compared to other techniques, regarding the multi-normality of the data [72,73].
To verify the quality of the model, the reflective measurement models that constitute the different factors considered were first analyzed and, later, the structural model was generated. The analysis of the measurement models includes their validity and reliability. Different fit and reliability indices were calculated to evaluate the global fit and adequacy of the posited model. A summary of the values obtained, and the values generally accepted [70] are shown in Table 3.

5. Results

According to the results, of the 15 hypotheses posited, 13 hypotheses are accepted with a confidence level higher than 99% (p < 0.01). H2 (travel organization-satisfaction) and H15 (expense-loyalty) have not been confirmed at the indicated confidence level, regarding p values, which is slightly lower, so niether hypotheses have been validated. Next (Table 4), the results for each hypothesis are presented:
In Figure 2, the proposed model scheme is graphically presented with the value of the estimated parameters followed by, in parentheses, its corresponding p-value and including the value of the coefficient of determination (R2) for each latent variable.
Next, the most significant results related to the stated hypotheses and the effects between the model’s factors are analyzed.
In the case of the loyalty factor (R2 = 0.11): tourist profile, organization of the trip, activities, and expense explain its behavior by 11%. The organization of the trip (β = 0.67, p < 0.01) is the factor with the greatest influence on the loyalty of the cultural tourist, followed by the activities carried out (β = 0.07, p < 0.01). On the other hand, a weak relationship between satisfaction and an increase in loyalty to the destination (β = −0.06, p < 0.01) indicates that greater general satisfaction with the visit/trip does not correspond with greater loyalty, but is slightly negative. Similarly, the level of spending has no influence on fidelity to destination (β = 0.00, p = 0.29).
The tourist profile, the organization of the trip, the activities, and the expenditure explain only 1% of the satisfaction behavior (R2 = 0.01). These variables have a weak relationship with satisfaction, the activities carried out at the destination have the greatest influence on the overall satisfaction of the cultural tourist (β = 0.26, p < 0.01). The tourist profile and especially the trip’s organization explain 47% of the behavior of the expenses (R2 = 0.47).
The organization of the trip has the most significant influence on the level of expenditure made by the cultural tourist (β = 0.67, p < 0.01), noting that the higher certain variables of the profile take, such as the cultural level, the lower the expenditure produced by the cultural tourist (β = −0.11, p < 0.01).
Profile, organization of the trip, and level of expenditure explain the behavior of the ‘activities’ variable by 35%. Expenditure is the one that has the largest influence on the number of activities carried out by the cultural tourist. Furthermore, the higher certain profile variables, such as age, the fewer activities are carried out by the cultural tourist (β = −0.03, p < 0.01).
Regarding the profile (β = −0.05, p < 0.01), the higher certain variables of the socio-economic profile (age or purchasing power), the lower the degree of organization of the trip; the contracting of closed packages is rejected in favour of the formula of “traveling at your own pace”. Besides, and as indicated above, the relationship between the variables considered is not linear. Next, some figures that show the behavior of specific variables of the model’s hypotheses were incorporated.
H5. Organization of the trip → Expense
The independent variable (travorg) influences the dependent variable (expenses). Except in cases where there is almost no organization of the trip (very low levels on the horizontal axis), the association with spending is clear, almost linear, in its central section, and positive. The progressive increase in the organization of the trip leads to an increase in spending. The use by the cultural tourist of tourist services, both for the organization of the trip and those contracted at the destination, entails an increase in spending (Figure 3).
H8. Socio-demographic profile → Activities
The relationship between profile and activities is weak and negative (β = −0.03, p < 0.01). The graph shows how the independent variable (“profile”) has a negative influence on the dependent variable (activ) in such a way that, as the socio-economic profile increases, the activities carried out in the destination decrease. The curve presented in the graph suggests a significant negative relationship for low and high levels of the socio-economic profile, with practically no constant variable relationship for medium levels of the profile (Figure 4).
H11. Satisfaction → Loyalty
Contrary to the posited hypothesis, the general satisfaction of the tourist with the trip influences the fidelity to the destination. However, the sign of satisfaction is negative, with a reduced effect (beta = −0.06) on the loyalty of the tourist (Figure 5). Furthermore, the graph shows this negative association for low and medium satisfaction levels and slightly upward between both variables for high levels. Therefore, greater satisfaction does not lead to greater fidelity to the destination on the part of the cultural tourist.
H15. Spending before and during the trip → Loyalty
The relationship is statistically non-significant (p = 0.29). If the curve in the figure is observed, an inverted “U” shape can be seen for the association of these two variables. Thus, medium-low spending levels would be associated with a growth in loyalty, and medium-high levels would be associated with decreased loyalty (Figure 6).

6. Discussion and Implications

The influence (β = −0.02, p = 0.02) of the socio-economic profile of the cultural tourist to the degree of satisfaction (H1) was confirmed. The cultural tourists have, in general, higher education, which makes it easier for them to be “closer” to the culture of the destination. In addition, this high educational level allows them to access, interpret and understand what they visit [74,75], facilitating a greater degree of general satisfaction.
The high purchasing power of this demand segment allows contracting personalized, exclusive, and high-quality tourism products that satisfy all the expectations generated by increasing general satisfaction.
The relationship between the highest number of activities carried out, and the degree of satisfaction (H3), confirms (β = 0.06, p < 0.01), in line with [76]. Thus, the experiences lived by the tourist when carrying out activities in the destination are compared with the projected expectations, resulting in his degree of satisfaction.
It shows how important destinations have a wide range of tourist attractions and complement offers that motivate cultural tourists to return to the destination. If the possibilities for new activities have been exhausted, even if the tourist experience has been positive, the visit may not be repeated. If the tourist values that he can live new experiences or carry out the same activities in the next visit, he could revisit the destination.
The weak influence (β = 0.01, p = 0.22) of the trip’s organization on the tourist’s general satisfaction (H2) stands out. However, its influence would not be as relevant as expected, derived from other studies on the positive influence of the organization of the trip on tourist satisfaction [41,77].
The increase in spending confirms (β = 0.04, p < 0.01) that it positively influences general satisfaction (H4). However, although it does not increase indefinitely with higher spending, it reaches a maximum point from which more spending implies lower satisfaction. Thus, although the customer makes an expense, it may happen that it does not imply a significant increase in his satisfaction, since the product’s characteristics are not relevant for the consumer [78].
The result obtained (β = 0.67, p < 0.01) suggests that a more outstanding organization of the trip implies an increase in spending (H5), offers information on the distribution of tourist spending before and during the visit. The Residents Tourism Survey [15] data on the organization of the trip shows that the cultural tourist hardly uses standardized, organized trips (tourist packages) but rather organizes the trip independently. It supports the explanation of the increase in the contracting of tourist packages as the physical and cultural distance between origin and destination increases [49]. Furthermore, this research analyzes the internal demand of the Spanish market, so the use of closed packages is much lower.
The higher educational level of the cultural tourist provides a more autonomous client, who does not use organized trips or standardized products, with the decrease in contracted activities [79].
The influence of the organization of the trip on the activities (H6) confirms the decrease in activities carried out at the destination (β = 0.07, p < 0.01) if the degree of organization of the trip increases [80]. Moreover, it shows the distribution of the increase or decrease in unorganized leisure time through tourist channels.
The cultural tourist seeks quality, personalized experiences, and deep knowledge of the destination, so they do not carry out activities exhaustively [74]. This explains that the organization of the trip can be high, but it does not involve the use of tourist services to carry out activities.
The confirmation of the positive relationship of the expenditure made, before and during the trip, on the activities carried out (H7), shows (β = 0.55, p < 0.01) that not only the income level influences tourism expenditure (a high purchasing power means carrying out more activities and a lower level of income fewer activities), but other variables influence expenditure as well. The psychographic aspects of the cultural tourist (personality, lifestyle, interests, hobbies, and values), the primary motivation of him to travel or the characteristics of the trip, which mediate the activities carried out in the destination, become relevant. In addition, not all cultural activities equally influence the total expenditure made [80].
The relationship between the profile and the activities carried out at the destination (H8), both qualitatively and quantitatively, is influenced by the new socio-economic characteristics of the postmodern cultural tourist (β = −0.03, p < 0.01). The higher educational level of the cultural tourist creates a more autonomous client who does not use organized trips or standardized products, reducing the contracted activities [79].
Furthermore, the results confirm that, as the socio-economic variables of the cultural tourists decrease, they have less purchasing power, they are less autonomous, and hire more organized activities to get to know the destination [67].
The importance of the socio-economic profile is also confirmed (β = −0.05, p < 0.01) in relation to the organization of the trip (H9) and the expenditure made (H10), influencing significantly (β = −0.11, p < 0.01) on what and how much is spent. H9 must be related to the statement about the influence of the socio-cultural profile of the cultural tourist and the activities carried out (H8) [79]. The result of the H10 agrees with the studies that indicate the importance of the socio-economic profile of the cultural tourist (high educational level and medium-high purchasing power) in the selective contracting of quality tourism services and bigger added value [48].
The negative relationship between the repetitiveness of the visit and a higher degree of satisfaction (H11), (β = −0.06, p < 0.01) is relevant, as it is a finding in the results obtained. Satisfaction may not have a linear effect on loyalty and buyback [81]. Although the tourist obtains a high degree of satisfaction, the search for new experiences influences the choice to revisit a destination [44]. The tourist can consume a destination as a product category. Although they are delighted with the cultural destination, they can visit other destinations with similar characteristics but not revisit them [82]. Therefore, tourists who visit a destination may present less satisfaction [83].
The positive relationship between the organization of the trip and loyalty (H12), (β = 0.26, p < 0.01) reveals the influence of the variables related to the mode of travel contracted or the type of group in the degree of fidelity to destiny. The commercialization of cultural tourist destinations must consider how the cultural tourists organize their trips, i.e., mostly on their own terms. It is about promoting the tourist services and resources that respond to this way of organizing the trip to facilitate their loyalty [42].
Moreover, the profile of the cultural tourist has an influence (β = 0.07, p < 0.01) on the loyalty to the destination (H13). It is the case of income where, at low levels, it can condition the loyalty of the tourist to the destination or, irrelevant, at the highest income levels [84].
The precise relationship (β = 0.12, p < 0.01) between the greater number of activities carried out and the increase in satisfaction (H14), suggests the importance of the diversity of tourist attractions and complementary offers of destinations, as it may be the incorporation of natural resources and rural tourism, which motivate the tourist to revisit the destination [85].
Concerning spending, the hypothesis of its influence on loyalty could not be established (β = 0.00, p = 0.0.29), (H15), so the creation of high-end tourist products/services cost does not mean greater fidelity to the destination [47].

6.1. Theoretical Implications

As a contribution of this study, a causal relationship model has been built. This model has already been verified empirically through quantitative methods, which explains the behavior of the internal demand of cultural tourism. In addition, this model has been validated, which allows for establishing forthcoming publications offering actions to increase satisfaction and loyalty to the destination of visitors whose primary motivation is culture.
A significant contribution of the study is the use of non-linear functions to test the relationships between the factors of the proposed model, which has made it possible to model the non-linear effects, contributing to a better approximation to reality.
The above provides a more sufficient knowledge base about the typologies and behaviors that predict a greater demand for cultural tourism. Results and conclusions for cultural tourism in Spain, given by the breadth of the national data analyzed from the Resident Tourism Survey, may become an excellent inspiration for extending the analysis to other contexts.

6.2. Practical Implications

Knowing the tourist who visits a destination implies greater chances to take action in destinations. The segmented investigation of visitors and their behavior provides information to the destination to define the type of tourism development required. This allows the design of various tourism strategies, such as those aimed at job creation, sustainable tourism growth, or tourism enhancement to its cultural resources. It also provides tools for creating and consolidating specific tourism products oriented to a specific type of demand more exigent with sustainability issues.
Some guidelines can be extracted from this analysis. They are essential for improving the destination of tourist flows or action plans oriented to the needs of the cultural tourist. This is the case of the type of travel organization used by the cultural tourist. The hiring of closed packages marks the use of tourist resources, spaces, and times in the destination that are much more limited than the trip “at your own pace”, the most commonly used form of tourism for cultural tourist.
It allows more effective sustainable management of cultural tourist destinations by helping tourism managers design promotion and positioning policies.
The marketing of destinations facilitates moving from market marketing (designed by tour operators) to destination marketing, designed by local agents, considering the needs of the resident population, thus generating sustainable tourism for the destination.
Knowing what factors influence the satisfaction and loyalty of the cultural tourist allows for expanding/redesigning the available cultural tourism offer, transforming it into sustainable cultural tourism products, and the design and configuration of cultural tourism products and their commercialization through differentiated marketing strategies that generate loyalty to the destination. This is the demand that repeats the visit and the need to value complementary offers, such as tourist resources associated with nature or intangible values, as sustainable places, for their loyalty.

6.3. Limitations and Future Research

The limitations of this research derive from the variables present in the Resident Tourism Survey.
The exploitation of statistics, framed within the general guidelines given by the UNWTO for the study of demand, requires a more operational adaptation by integrating concepts and certain variables adapted to the needs of cultural tourism. The indicators used to measure satisfaction analyze the degree of general satisfaction, but not by attributes. Fidelity is not addressed as a multidimensional variable. This does not allow the analysis of future behavioral intentions, such as the recommendation to third parties of the destination.
It would also be accurate to use fewer general variables to analyze primary motivation. In the case of cultural tourism, a single variable encompasses all cultural motivations.
Finally, it would be necessary to analyze the influence of other indicators on the behavior of the cultural tourist, since those chosen are based on the variables present in the questionnaire.
To complete an even broader study of the behavior of cultural tourists in the future, it would be convenient to study the different demand segments within cultural tourism in greater depth. In addition, to analyze other variables that influence the behavior of the cultural tourist (the image projected on the destination), as well as to apply the model to different types of tourists and destinations, would allow an extension of our field of research (as, for example, nature or sun and beach).
In this study, we confirmed that satisfaction as a precedent of the fidelity of the cultural tourist may not materialize in a repetition of the visit. Therefore, it could be interesting to investigate the relationship between satisfaction and intention to repeat the visit and the recommendation of the destination to third parties.

Author Contributions

M.-D.S.-S. has developed the theoretical framework; C.D.P.-H. has provided the discussion and conclusions and J.-L.M.-B. has done the statistical analysis. All authors have read and agreed to the published version of the manuscript.

Funding

This article has been funded with the project research V946, DICORELA: Contribution of dialogic practices to the quality of teamwork: a proposal for the evolution of the relational coordination model.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data set associated with the paper will be provided on demand.

Conflicts of Interest

The authors report no conflict of interest.

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Figure 1. Posited model. Source: Own elaboration.
Figure 1. Posited model. Source: Own elaboration.
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Figure 2. Model parameters and determination coefficients. Source: Own elaboration.
Figure 2. Model parameters and determination coefficients. Source: Own elaboration.
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Figure 3. Hypothesis 5. Source: Own elaboration.
Figure 3. Hypothesis 5. Source: Own elaboration.
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Figure 4. Hypothesis 8. Source: Own elaboration.
Figure 4. Hypothesis 8. Source: Own elaboration.
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Figure 5. Hypothesis 11. Source: Own elaboration.
Figure 5. Hypothesis 11. Source: Own elaboration.
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Figure 6. Hypothesis 15. Source: Own elaboration.
Figure 6. Hypothesis 15. Source: Own elaboration.
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Table
Table 1. Sample.
Table 1. Sample.
Survey TypeContinuous Every Quarter
Population scopePopulation over 15 years of age that resides in the main family dwelling
ScopeThe entire national territory
Reference periodMonthly
Sample sizeAround 16,400 interviews conducted each month
Information gatheringTelephone interviews and, in some cases, personal interviews
Source: National Institute of Statistics 2018.
Table
Table 2. Shows the sample characteristics.
Table 2. Shows the sample characteristics.
Sample Characteristics
Data usedResident tourist survey/Familitur
Data analyzedTravels of cultural motivation with destiny in Spain
Reference periodFebruary to September 2018
Sample Sizen = 18,024
Source: Own elaboration.
Table
Table 3. Model fit and reliability indices.
Table 3. Model fit and reliability indices.
IndexValueValue Interpretation
Average path coefficient (APC)APC = 0.161, p < 0.001Significant if p < 0.05
Average R-squared (ARS)ARS = 0.208, p < 0.001Significant if p < 0.05
Average adjusted R-squared (AARS)AARS = 0.208, p < 0.001Significant if p < 0.05
Average block VIF (AVIF)AVIF = 1.278Acceptable if ≤ 5, ideally ≤ 3.3
Average full collinearity VIF (AFVIF)AFVIF = 1.437Acceptable if ≤ 5, ideally ≤ 3.3
TenenhausGoF (GoF)GoF = 0.281Small ≥ 0.1, medium ≥ 0.25, large ≥ 0.36
Sympson’s paradox ratio (SPR)SPR = 1.000Acceptable if ≥ 0.7, ideally = 1
R-squared contribution ratio (RSCR)RSCR = 0.1.000Acceptable if ≥ 0.9, ideally = 1
Statistical suppression ratio (SSR)SSR = 1.000Acceptable if ≥ 0.7
Nonlinear bivariate causality direction ratio (NLBCDR)NLBCDR = 0.600Acceptable if ≥ 0.7
Source: Own elaboration.
Table
Table 4. Assessment of the hypotheses.
Table 4. Assessment of the hypotheses.
H1Sociodemographic profile → Satisfaction (β = −0.02, p = 0.02)Confirmed hypothesis.
H2Travel Organization → Satisfaction (β = 0.01, p = 0.22)Unconfirmed hypothesis.
H3Activities carried out → Satisfaction (β = 0.06, p < 0.01)Confirmed hypothesis.
H4Spending before and during the trip → Satisfaction (β = 0.04, p < 0.01)Confirmed hypothesis.
H5Organization of the trip → Expenditure (β = 0.67, p < 0.01)Confirmed hypothesis.
H6Organization of the trip → Activities (β = 0.07, p < 0.01)Confirmed hypothesis.
H7Expenditure before and during the trip → Activities (β = 0.55, p < 0.01)Confirmed hypothesis.
H8Sociodemographic profile → Activities (β = −0.03, p < 0.01)Confirmed hypothesis.
H9Sociodemographic profile → Organization of the trip (β = −0.05, p < 0.01)Confirmed hypothesis.
H10Sociodemographic profile → Expenditures incurred (β = −0.11, p < 0.01)Confirmed hypothesis.
H11Satisfaction → Fidelity (β = −0.06, p < 0.01)Confirmed hypothesis.
H12Organization of the trip → Fidelity (β = 0.26, p < 0.01)Confirmed hypothesis.
H13Sociodemographic profile → Fidelity (β = 0.07, p < 0.01)Confirmed hypothesis.
H14Activities carried out → Fidelity (β = 0.12, p < 0.01)Confirmed hypothesis.
H15Spending before and during the trip → Loyalty (β = 0.00, p = 0.29)Unconfirmed hypothesis.
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MDPI and ACS Style

Sánchez-Sánchez, M.-D.; Pablos-Heredero, C.D.; Montes-Botella, J.-L. The Internal Demand of Cultural Tourism: Understanding Satisfaction and Fidelity to Destination in Spain through a Non-Linear Structural Model. Sustainability 2021, 13, 13487. https://doi.org/10.3390/su132313487

AMA Style

Sánchez-Sánchez M-D, Pablos-Heredero CD, Montes-Botella J-L. The Internal Demand of Cultural Tourism: Understanding Satisfaction and Fidelity to Destination in Spain through a Non-Linear Structural Model. Sustainability. 2021; 13(23):13487. https://doi.org/10.3390/su132313487

Chicago/Turabian Style

Sánchez-Sánchez, María-Dolores, Carmen De Pablos-Heredero, and José-Luis Montes-Botella. 2021. "The Internal Demand of Cultural Tourism: Understanding Satisfaction and Fidelity to Destination in Spain through a Non-Linear Structural Model" Sustainability 13, no. 23: 13487. https://doi.org/10.3390/su132313487

APA Style

Sánchez-Sánchez, M. -D., Pablos-Heredero, C. D., & Montes-Botella, J. -L. (2021). The Internal Demand of Cultural Tourism: Understanding Satisfaction and Fidelity to Destination in Spain through a Non-Linear Structural Model. Sustainability, 13(23), 13487. https://doi.org/10.3390/su132313487

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