Sustainable Development and Consumer Behavior in Rural Tourism—The Importance of Image and Loyalty for Host Communities

Abstract

In recent years, rural tourism has experienced a major boom; it was once a secondary type of tourism but has now become a significant alternative option within the Spanish economy. This type of tourism facilitates the sustainable development of the host communities and their surrounding areas, becoming an extra source of income in some cases, and the principal business in others. It is therefore important to ascertain which variables influence the behavior of rural tourists. The objective of this study is to demonstrate the influence on rural tourist behavior of destination image, both initial and final, as well as tourist satisfaction and loyalty to the area. Loyalty, which translates into repeat visits to the area and recommendations to third parties, promotes the sustainable development of rural areas. After an exhaustive review of the literature on the relevant variables, an empirical study was carried out using a questionnaire designed for tourists over 18 years old who visited the province of Soria (Spain) and stayed in a rural tourism establishment. This resulted in a total of 1658 valid completed questionnaires. A structural equation model was then drawn up to discover the relationships between all the variables. The results demonstrated the importance of destination image in the formation of the new image, and also showed that tourist satisfaction is the variable that most strongly influences loyalty to the tourist area. This study is a novel contribution to the study of sustainable development in rural areas since it focuses on tourist loyalty and its resulting benefits.

1. Introduction

The present study is an original investigation of the behavior of rural tourism consumers. This behavior should ideally be in line with the Sustainable Development Goals defined by the UN in 2017, especially goal 8—Decent Work and Economic Growth—which promotes inclusive and sustainable economic growth, employment, and decent work and economic growth for all, which in turn drive progress and improve living standards. This sustainable tourism should lead to an improvement in the socio-economic conditions of the population visited by this type of tourism. It should result in environmental maintenance that not only attracts new tourists but also generates loyalty in those tourists who have already visited the area. These will be the topics of this analysis. This study will convince the government bodies in charge of managing rural tourism of the need to promote those tourist areas with the greatest need, not only in economic terms but also due to depopulation and lack of jobs. The academic world will also benefit from this article, since it provides a statistical model for analyzing and studying how the image of a tourist destination and tourist satisfaction with that destination can influence the loyalty of rural tourists, increasing future visitor numbers and thus contributing to sustainable economic and social development.

In recent years, rural tourism has been developing faster than other types of tourism [1]. The motivations and behaviors of these types of tourists are very different from those of tourists involved in conventional tourism. The motivations that affect the conventional tourist, as explained by Crompton [2] and expanded by Crandall [3], are of two types: sociopsychological (escape from the routine, self-exploration and evaluation, relaxation, prestige, regression, improvement of family relationships, and facilitating social relations) and cultural (novelty and education). The motivations that drive rural tourists, which are a variant on the motivations of the general tourist, are, as explained by Lois et al. [4], Tirado [5], Devesa et al. [6] and Leco et al. [7], related to nature, culture, and the environment. These authors gave a list of ten essential motivations in rural tourists, which are: contact with nature; rest and tranquility; purity of air and water; open spaces and a healthy environment; gastronomy; agricultural activities; discovering another culture; the kindness and hospitality of the local population; contact with architectural, ethnographic, and material heritage and the opportunity to “travel to the past” while enjoying the comforts of the present. For Polo [8], rural tourism is the activity through which tourist experiences are provided that integrate the necessary elements and services to provide a comprehensive leisure offering to tourists, while including aspects that differentiate the experience of rural tourism from other types of tourism. This author also considers that the development of this type of tourist activity is very suitable for improving the development of rural areas. This is a recurring theme in rural tourism literature. According to García [9], rural tourism harmonizes the interests of tourism, the environment, and the local community. Likewise, Marzo-Navarro [10] stated that rural tourism promotes the development and economic growth of the destination areas, for which it is a priority to achieve the objectives of economic, socio-cultural, and environmental sustainability. The UNWTO [11] has recognized that “tourism is one of the driving forces of global economic growth and is currently responsible for the creation of 1 in 11 jobs. By giving access to decent work opportunities in the tourism sector, society—in particular, young people and women—can benefit from improved skills and professional development. The sector’s contribution to job creation is recognized in target 8.9: By 2030, devise and implement policies to promote sustainable tourism that creates jobs and promotes local culture and products.” The UNWTO itself also recognizes that tourism can contribute to all sustainable development goals, but more specifically to goals 8, 12, and 14.

Concepts of the rural environment have changed substantially. It used to subsist solely through agriculture but is now increasingly based on a service economy. The traditional function of these areas, namely agriculture, has become secondary, thus transforming them into multi-functional spaces [12,13,14]. Similarly, traditional industries in rural areas can complement their activities with tourism, creating a tourism product that responds to the demand for new experiences [15]. This type of tourism must therefore be developed and promoted since it encourages the rural population to remain in the area. Rural tourism may well represent the best model for the sustainable development of the tourism sector. This tourism values cultural and local festivities and other cultural events and integrates the local population into the products offered, thus improving the quality of life of the local population [1]. For Reyes-Aguilar et al. [13], it is an alternative income-generating activity that assists locations with great natural and cultural potential, as well as a response to the problems of the rural environment in general. In this context, rural tourism can become a solution to the economic and social problems of the most depopulated rural areas, and generate sustainable development in these areas.

Sustainable development as a concept emerged in the early 1990s, in response to the need to counterbalance uncontrolled and unplanned development [16]. It was defined by the United Nations World Commission on Environment and Development in 1998 as “that development that satisfies the needs of the present, without endangering the ability of future generations to satisfy their own needs, that is, among the characteristics included in any sustainable development process is that of defending equity and social solidarity.” This definition contains two key concepts that are very interesting. First, sustainable development must provide a future for the next generations; and second, there must be social development. Extensive development of rural areas is necessary to ensure that future generations living in depressed areas with a high degree of depopulation can have a promising future without having to leave the areas where they were born and raised. This development is also necessary to ensure economic sustainability that contributes to avoiding an exodus to urban areas and thus promotes local and traditional economies [17]. This sustainable development should translate into an improvement in the quality of life of the local population and offer a higher quality of experience for the visitor, to achieve social and cultural enrichment for both visitors and the local population [18,19], as well as an increase in community income [20,21,22].

A development project should not be conceived if it is not sustainable, in other words, if it does not maintain equity between all the dimensions that comprise it (social, economic, and environmental). This is because it is necessary to think and act with a desire for development, but with expectations of future sustainability [23]. The sustainable development process must contemplate global management of resources to ensure their durability, making it possible to conserve the natural and cultural capital of each area [24]. These same authors consider tourism to be a powerful development instrument that can and should actively participate in this sustainable development strategy. The principles of sustainability assume that the social well-being of local economies must be linked to tourism development [25] because tourism offers greater possibilities for sustainable human development than other sectoral interventions [26]. Sustainable tourism development responds to the needs of the present tourists and host regions while preserving and promoting opportunities for the future [27]. There must be a harmonious balance between the needs of visitors and residents [28,29] since these residents can be considered to constitute one of the principal stakeholder groups in successful tourism development [10]. Consequently, tourism is a wealth-generating activity and seeks to make this development socially responsible [24,30].

In rural areas, the type of tourism that can contribute very significantly to this sustainable development is rural tourism. A local tourism offering must therefore be structured that will be an important factor in the development over the medium and long term [31,32]. Tourism is considered vital for the economic welfare of rural communities [33]. Moreover, as De Jesús-Contreras and Thomé-Ortiz [34] indicate, wine tourism is a more modern type of tourism that assists the development of rural tourist areas that are associated with the wine industry. For Baraja et al. [35], over the last four decades, the wine sector and wine tourism have become key components of the rural economy in many areas of Spain. This is because they have a considerable social impact, by generating a very significant number of jobs. They also have a positive territorial impact, because the vast majority of these jobs are generated in rural areas. In the same vein, López Guzmán et al. [36] emphasize the importance of wine tourism to rural economies. Zamarreño-Arramendía et al. [37] add that it is important to promote quality wine production. As Martínez and Blanco [1] indicate, tourism will generate employment for the residents of rural tourist areas and will prevent the exodus of the population to other more developed areas in search of jobs. This increased employment is closely related to the development of sustainable tourism, highlighting elements such as the involvement of the local population of the specific area. It thus offers them a means of livelihood through job creation [16].

Sustainable rural tourism is, consequently, an activity that contributes positively to the local and economic development of rural areas and at the same time does not negatively affect the natural and social environments [38]. This local development can be defined as the localized process of ongoing socioeconomic change that, led by local governments, integrates and coordinates the use of wealth, to achieve local progress and human well-being, in balance with the natural environment [39]. This type of tourism, therefore, improves the sustainable development of rural economies [40,41,42]. But it is also important to analyze the negative socioeconomic effects that tourism has on the destination areas. Orgaz and Cañero [43] exposed the risks that rural tourism has for local populations. These include the loss of cultural identity, the deterioration of cultural and natural resources, as well as the impact that the creation of infrastructures has on the local populations. Orgaz [44] also discussed this issue, since for this author the type of changes to flora and fauna, as well as environmental contamination were significant. Other authors such as Brunt and Courtney [45] and Gursoy and Rutherford [46], also spoke about the possible negative impacts of rural tourism in destination areas.

Rural tourism must achieve the conservation of the resources on which it is based and improve the quality of life of local residents [10]. It is a key tool for the development of certain regions [47,48,49] that should serve to implement a sustainable socio-economic reactivation and, through the commercialization of local products, will serve to enrich the social, cultural, and economic level of the area [1,50,51,52].

Summary, the present study, is an original study on the link between loyalty in rural tourism and its influence with the SDGs, especially Goal 8. The reason for this study is to help the different administrations responsible for tourism to take correct decisions to promote the sustainable development of rural areas through tourist loyalty. For this, a large study has been carried out developing a model of rural tourist behavior.

2. Conceptual Framework and Hypothesis

2.1. Research Framework

Tourism, and especially rural tourism, has become an engine of local development. This type of tourism increases the well-being of the local population [23,53,54,55,56,57] as it provides long-term sustainable business, thus creating socio-cultural benefits, stable employment, and contributing to poverty reduction while giving high levels of satisfaction [58]. It should be remembered that the tourism industry is the largest and most important industry worldwide in terms of the number of employees [59]. It can be a tool in the fight against poverty [26,60,61], as it improves the living conditions of the local population. This is mainly because it is complementary to agriculture, as we have mentioned, and an alternative source of income [62]. This sector is considered a tool for social inclusion, a generator of work and youth employment, and a source of well-being [63]. It brings great benefits to rural areas as it directly impacts local families and their lifestyles [64]. Rural tourism should be considered to be a factor in local development and encouraged as a vital development objective in terms of improving people’s quality of life [28,65,66] since it does not negatively affect the local population [1]. This type of tourism should also contribute to revitalizing the economy, to improve the local population’s standard of living [16,67].

Rural tourism development must therefore meet the needs of the host community [68,69] and achieve the following requirements: foster social inclusion and youth employment [16,70]; be an alternative for diversifying and restructuring rural areas [71,72]; promote environmental conservation and improve understanding of the cultural values of the different locations [63,73]; and generate wealth for local residents [13,24,74].

However, this is not the only benefit of rural tourism development. In recent decades, it has become a route for women to access the labor market [75]. Women in rural areas are involved in the processes of renewing the economic life of the towns and must therefore acquire a leading role as development agents [13,76,77,78,79,80].

Over the recent decades, the management of rural tourism, by both the owners of rural accommodation and the different administrations, has been focused on promoting their destinations [63], although not adequately in all cases [81].

These tourist areas must have natural resources on which to base strategically planned tourist development [10]. These resources are any natural element that could be the motivation for a tourist trip. As Alonso-Almeida and Celemín-Pedroche [82] state, these resources provide the experience that rural tourists have been seeking of late, associated with sustainability. However, for this type of tourism to act as a factor for local development, it is vital to know how to protect the quality of the environment, since it is the beauties of nature that make this activity possible [28]. This sustainability must constitute the strategic objective for any destination [83,84] and is the key variable in achieving its competitiveness [85]. The sustainability of tourist destinations has become a key differentiating element that increases competitiveness [86].

Many rural areas are perceived, thanks to the image of the destination that they promote to the world, as having a high tourist potential as there are resources such as natural landscapes, cultures, traditions, the opportunities for outdoor activities, and gastronomic experiences. If this destination image, this tourist attraction, is promoted intelligently, it can translate into a large tourist influx that generates economic income, wealth, and social and economic sustainability [1]. As Linares and Morales [28] explain, tourism sells a landscape. But this rural tourism potential must also be reflected in the preservation of natural resources, since they must be maintained over the years, to achieve long-term sustainable social development [16]. Visitors and tour operators in rural areas must have a very clear image and perception of the tourist areas, to determine how this type of tourism can contribute to the sustainability of a rural area, since an ideal image perceived a priori, which tourists have obtained through tourist brochures and other types of advertising, is compared with the final or posterior image or perception [87]. Visitors, continues this author, have an idealized image of rural areas, which translates, after the trip, into a modification of their initial image.

We therefore see how important a definition of the image the destination shows to the world is, since a real and clear image that is not idealized will translate into a better final destination image that tourists will take away from the area. This in turn will result in greater tourist satisfaction with the destination and loyalty both to the rural accommodation and the rural area. This loyalty is key to the social and economic sustainability of the area since, as we have seen, increasing numbers of visitors, as well as the degree to which tourists who already know the area return for repeat visits, favors and is a key tool in the development and economic growth of the destination areas [10]. These outcomes also generate well-being in the populations of the destination areas [1,88]. All this is in accordance with achieving SDG 8.

In summary, as we can see in Figure 1, the main objective of this study is to analyze those variables that have the most influence on tourist loyalty to the area. This model summarizes the relationships between the different constructs described in the hypotheses. It is observed that the prior destination image does not influence loyalty to the location, but is essential to create satisfaction with the destination and is the basis for generating a new destination image, once the tourist area has been visited. These two variables (satisfaction and new destination image) influence loyalty and future visits to the tourist destination. As explained by Kastenholz et al. [89] and Prados-Peña et al. [90], loyalty is one of the main factors in the long-term success of a tourist destination, and is therefore important for the sustainable development of rural destinations.

2.2. Research Hypothesis

What do we understand by the image of the tourist destination? For Baloglu and MCleary [91], the destination image is “an individual’s mental representation of knowledge (beliefs), feelings and global impression about an object or destination.” For these authors, the destination image is made up of the cognitive part, which is that which we obtain through knowledge; the affective part, which is that which we obtain through our feelings; and the overall part of the image, which is the sum of both components. They therefore divided the image into two components, the cognitive and the affective, which together make up what is known as the overall destination image. Most authors emphasize this division into two image components [92]. Sanz [93] defined destination image as “the global perception of a destination, in other words, the representation in the tourist’s mind of what he or she feels and knows about it.” Others have analyzed the differences between affective image, which is much more volatile, and cognitive image, which persists [94], and explained that the differentiation between both components allows us to understand how tourists value places. For Machado et al. [95], the destination image, both affective and cognitive, tends to strengthen after the visit. The destination image is therefore made up of two components: the cognitive and the affective. Both influence what we know as the destination image, or the overall destination image. We can define the image of the destination as the overall mental impression each person has of a place or destination formed by knowledge as well as by the feelings the destination produces in them.

This image is a key element in choosing a tourist destination. For Fakeye and Crompton [96], the decision process for a tourist destination goes through several phases. First, initial images of the different places that could be chosen as the final destination are formed in the tourist’s mind. An induced image is then formed from the various sources of information available. This image is much more formal and consistent. After this, the different benefits provided by each destination and the images that have been constructed are evaluated and a destination is selected. Likewise, Gunn [97] indicates that first an image about the destination is generated based on previous information (documentaries, experiences of acquaintances, etc.,) and later, thanks to promotional information such as promotional brochures, an induced image is formed. This image is what helps the individual to choose a destination. Today, the use of ICT helps people to plan their holidays and obtain detailed information about the destination [98]. Social networks in particular act as a tool to assist in making this choice, as well as facilitating interrelationships between stakeholders [99].

It is, therefore, necessary that this destination image be promoted coherently and rationally, so that potential tourists consider it when choosing the place as a tourist destination. Bolan and Williams [100] referred to the role that image plays in tourism promotion and, therefore, in choice. Consumers are very sensitive to destination image, therefore—to some extent and sometimes—potential tourists choose the destination based on the image they have formed of the place. According to García [101], word of mouth is the best promotion in rural tourism. Recommendations from family and friends are the main source of information both when deciding where to travel and when planning the trip. Currently, as Casaló et al. [102] comment in their study, rural tourists search for information on the Internet, and the use of social networks in this search has increased. The most important factor is trust in that network and in the type of information that they obtain. Social networks therefore replace the functions previously fulfilled by travel agencies and organizations. We now look for information from other consumers. This information, especially when searching through social networks, focuses on images, specifically an attractive destination image. The direct relationship between destination image and loyalty is therefore clearly shown.

After defining the destination image and differentiating between its two components, we define the following as first hypotheses:

Hypothesis 1a (H1a).

Cognitive image has a positive influence on image as a dimension.

Hypothesis 1b (H1b).

Affective image has a positive influence on image as a dimension.

This destination image, however, is not fixed but is in continuous transformation. After the visit, the definitive image is formed. This is referred to as the modified induced image, created by the tourist’s personal experience [97]. Gunn [97] explains the new destination image that the tourist forms after visiting the place. Sanz [93], for her part, analyzed destination image and concluded that the initial destination image is what attracts a tourist to the place, but after the visit, there is a modification of this initial image, which, if it is positive, enhances the brand loyalty to that place. Lima and Costa [103] also differentiated between the initial image (defined by these authors as imaginary) which is that generated by the tourist from a set of information generated in his or her imagination (cognitive destination image); and the final image, which is the one generated after the visit, which is referred to when communicating and informing about the tourist destination, i.e., in word-of-mouth marketing.

The link between the prior destination image and satisfaction has also been studied extensively. For Rajesh [104] and Machado et al. [95], the destination image has a direct influence on both general satisfaction and loyalty to the destination. Nysveen et al. [105] also addressed this relationship but focused on the green destination image. Olague [106] explained how the tourist’s motivations, as well as the destination image, are directly linked to satisfaction with the visit. Martín et al. [107] and Battour et al. [108] also focused on the study of this relationship.

Based on the relationship that seems to exist between the destination, tourist satisfaction and the new destination image generated after the visit, we propose the following hypotheses:

Hypothesis 2a (H2a).

Image has a positive influence on satisfaction.

Hypothesis 2b (H2b).

Image has a positive influence on new image.

Regarding loyalty to the destination, numerous works analyze the behavior of tourists based on their loyalty [109,110,111,112,113,114,115]. Authors such as Lee [116] showed that the destination image indirectly affects loyalty, that in this case, it is the new destination image generated after the trip that provides all the influence. Sanz [93], also explained the direct relationship between the final destination image—generated after the visit—and loyalty to the tourist area.

In this regard, several studies consider the direct relationship between the final image and loyalty to the destination. O’Leary and Deegan [117] and Machado et al. [95], focused on the direct relationship between the final image and loyalty. Medina et al. [118] analyzed the direct influence of the final destination image on loyalty and concluded that a loyal tourist will have a greater propensity to visit the destination again and say positive things about it. Hong et al. [119] maintained that the image was very important on a second visit, since that image manages the behavior after the first visit. For them, decision-making after the first visit is completely different from decision-making after the second visit. Hutchinson et al. [114] also considered the relationship between satisfaction, the final destination image, and the intention to revisit a place.

In terms of the social and economic sustainability of tourist areas, it is very important to study this relationship intensively, since, as Kastenholz et al. [89] and Prados-Peña et al. [90] stated, loyalty is one of the principal factors in the sustainable development of rural destinations. It thus assists in achieving goal 8 of the Sustainable Development Goals. Not only is it necessary to promote a good image of the place, but, for the level of satisfaction to be high, this promotional or initial destination image must be the closest thing to the final image that the tourist generates after the visit, as this will generate loyalty to the destination [120]. Chon [121] concluded that if the image held by the rural tourist (initial image) and the image received at the destination (final image) are the same or similar, satisfaction with that destination will be very high. That satisfaction has a positive influence on the next visit to the destination since it creates loyalty. It also has a positive influence on the new destination image formed after that second visit. Kozak and Rimmington [122] and Alén and Fraiz [123] also presented a model of tourist behavior in which they found a direct relationship between satisfaction and loyalty. Rajesh [104] carried out a study in which he, too, developed a model of tourist behavior. He specified the relationship between the satisfaction that tourists take from the trip and the new image generated, as well as between satisfaction and destination loyalty.

We therefore propose the following study hypotheses:

Hypothesis 3a (H3a).

Satisfaction has a positive influence on new image.

Hypothesis 3b (H3b).

Satisfaction has a positive influence on loyalty.

Hypothesis 4 (H4).

New image has a positive influence on loyalty.

3. Methods

3.1. Survey Design

This research is based on a descriptive study using primary data from a questionnaire used on a representative sample of tourists over 18 years old who visited the province of Soria (Spain) and stayed in a rural tourism establishment. As you can see in Figure 2, the province of Soria is located in the north of Spain, east of the Autonomous Community of Castile and León and just two hundred kilometers from Spain’s capital, Madrid. It has a very diverse landscape, as well as countless historical and archaeological sites. It is the province of Spain with the lowest number of inhabitants (88,636 inhabitants in 2019). It is also the province that receives the second-lowest number of tourists in the entire country (233,203 tourists in 2019).

The total number of valid questionnaires collected was 1658, which implies a sampling error of ±2.45% with a confidence interval of 95.5% and p = q = 0.5 (See

Table 1. Technical details of the study.

-Universe: tourists aged over 18 who stayed in a rural tourism establishment

-Places where interviews were conducted: La Laguna Negra Natural Park, Vinuesa, Calatañazor, Yanguas and Garray villages, The Lobos River Canyon

-Field work: From January 2016 to January 2017

-Geographical scope: provincial (Spanish province of Soria)

-Sample size: 1658 valid questionnaires

-Sample design: structured questionnaire, anonymous. Personal interview

-Sampling error = 2.45% with 95.5% confidence level and p = q = 50%

).

The questionnaire is composed of eight main sections. The first part reflects the data referring to the respondent’s experience of the destination area. The second part studies the image that the tourist had of the area before the visit. The third part focuses on the respondent’s preferences regarding the type of tourism to be carried out. The fourth deals with the different motivations that caused the surveyed tourists to visit the area. The fifth dealt with the respondent’s lifestyle. The sixth part focuses on attitudes before and after the visit. The seventh studies the tourist’s satisfaction, the new image generated after the visit, and the probability of visiting the province again. All the items in the questionnaire were selected after an exhaustive bibliographic review and used the same four-point Likert scale, where 4 = a lot and 1 = little, except for the affective image and satisfaction items, where the scale was a Likert scale of five points from 5 = strongly agree to 1 = strongly disagree (see

Table 2. Scales of the model’s constructors.

Construct and Items	Sources of Adoption
Cognitive Image (COI)
I identify the province of Soria with ease of playing sports
I identify the province of Soria with a favorable climate
I identify the province of Soria with opportunities for adventure		[91]
I identify the province of Soria as aimed at both adults and families
I identify the province of Soria as having good road communication networks in the area
Affective image (AFI)
I identify the province of Soria with relaxation		[91]
I identify the province of Soria with pleasant
New image (NEI)
How did your overall image of the province change before you visited it?		[93]
Satisfaction (SAT)
You can value, in terms of satisfaction, your visit to the province of Soria		[116]
Considering your expectations, as you would value the experience in the province
Loyalty (LOY)
Do you plan to visit the province again another time?		[109,110,111,112,113,114,115]

).

A pre-test of this questionnaire was performed on 50 people who had visited the province and stayed in a rural tourism establishment. This was done to evaluate whether the scales were well constructed and the multiple questions on the questionnaire were understood. After checking that everything was correct, the data were collected personally in the tourist areas of Soria province. A sample of 1658 valid fully representative questionnaires was obtained.

3.2. Sample Size and Composition

The total sample consisted of 1658 valid questionnaires of visitors over the age of 18 who were staying in a rural tourism establishment in the area.

Table 3. Sample information.

Age	%	Education Level	%
18–35	20.08	Primary	23.52
36–45	46.14	Secondary	33.23
46+	33.77	University	43.24
Marital status	%	Occupation	%
Single	21.59	Employed	69.12
Married	41.38	Unemployed	29.55
Separated/divorced	10.37	Other	1.32
Living as a couple	26.54
Widow(er)	0.12
Gender	%
Male	51.75
Female	48.25

shows the sample information.

3.3. Statistical Analysis

The purpose of analyzing the information collected is to transform it into relevant information that assists the decision-making process. Several statistical techniques were applied, including principal component analysis, and a model was created using partial least squares structural equation modeling (PLS-SEM). The programs used were IBM SPSS Statistic, DYANE 4 [124], and SmartPLS 3.2.28 [125]. Hair et al. [126] recommended the use of PLS-SEM if the research is exploratory or an extension of an existing structural theory. Hair et al. [127] also recommend its use when the formative constructs are part of the structural model, the model is complex (many constructs and many indicators) and the data follow a non-normal distribution.

To facilitate the analysis of some of the variables studied, we carried out a factor analysis using principal component analysis (PCA), which is a factor analysis technique that reveals dimensions or underlying factors in the relationships between the values analyzed [128]. In our study, we have used this technique to reduce the number of variables of the destination image constructs, since they have a large number of variables. After carrying out this technique, the cognitive destination image, which started with thirty-one variables, was reduced to five; “tourist variety versus situational elements,” “interesting culture,” “fun and luxury,” “rest and interesting environment,” and “attractive accommodation.” Regarding the affective image, we went from four to two variables: “internal affective image” and “external affective image.”

Partial least squares (PLS), a structural equation modeling (SEM) tool, is used to perform the analyses. PLS-SEM opens up a valuable means of analyzing latent constructs that are designed from a composite of indicators. The first basic latent variable is called a first-order variable. Using these first-order variables, it is possible to build structures of how each component of these variables affects the others. In this model, there are five reflective first-order latent variables and they are cognitive image, affective image, satisfaction, new image, and loyalty. However, the model could be used to attempt to measure a higher level of abstraction by simultaneously including several subcomponents, which cover the more concrete traits of this construct. This is a model that establishes a higher-order model or hierarchical component model (HCM). In this case, there is a second-order variable and it is a formative second-order latent variable (image) that is determined by affective image and cognitive image. PLS is a variance-based technique that is often considered more appropriate than covariance-based modeling techniques when the emphasis is to develop a new model, because PLS is the more flexible method. It is also more appropriate when one or more formative second-order latent variables are used.

4. Results

4.1. Measurement Model: Reliability and Validity

Reliability and validity are related to each other, and they would be the first step in a partial least square (PLS) analysis. The way for assessing the reliability is to determine how each item relates to the latent constructs (

Table 4. Constructs and loadings.

Construct	Item	Loading
	I identify the province of Soria with ease of playing sports	0.84
	I identify the province of Soria with a favorable climate	0.91
Cognitive Image (COI)	I identify the province of Soria with opportunities for adventure	0.64
	I identify the province of Soria with aimed at both adults and families	0.77
	I identify the province of Soria with good road communication networks in the area	0.79
	I identify the province of Soria with relaxation	0.77
Affective Image (AFI)	I identify the province of Soria with pleasant	0.76
New image (NEI)	How did your overall image of the province change before you visited it?	1.00
	You can value, in terms of satisfaction, your visit to the province of Soria	0.81
Satisfaction (SAT)	Considering your expectations, as you would value the experience in the province	0.91
Loyalty (LOY)	Do you plan to visit the province again another time?	1.00

). In our five distinct first-order latent constructs, each of the scales consists of reflective items. To assess a measure’s reliability, we have used the rule of thumb of accepting items with loadings of 0.707 or more. All of the loadings in this study exceed 0.76 for these items (except for one variable in the cognitive image construct), and load more highly on their own construct than on others [126]. When one loading is under the said minimum value, loadings of at least 0.5 are acceptable [129], and this is more necessary if without this variable the average variance extracted (AVE) value is decreasing. These results provide strong support for the reliability of the reflective measures because all first-order latent constructs were constructed with reflective measures. The main reason why this option was selected is that the effects when items are removed do not affect content validity, and the items are correlated. Cronbach’s alpha and composite reliability (CR) assess internal consistency. As shown in (

Table 5. Internal consistency and AVE.

	Cronbach’s Alpha	Average Variance Extracted (AVE)	Composite Reliability
Cognitive Image (COI)	0.85	0.64	0.89
Affective Image (AFI)	0.70	0.59	0.74
New image (NEI)	1.00	1.00	1.00
Satisfaction (SAT)	0.68	0.75	0.86
Loyalty (LOY)	1.00	1.00	1.00

), Cronbach’s alpha values of around 0.7 are acceptable. It is possible to increase the α coefficient simply by increasing the number of items in the analysis. Using the CR value is therefore recommended. A CR value of 0.70 is suggested as a “stricter” degree of reliability, which is applicable in basic research [130]. For this internal consistency, the AVE is also used, and a value at least equal to 0.5 is recommended (for all the coefficients of each set of reflective measures in the study, the AVE exceeds 0.5).

At this point, it is necessary to show that the measures should not be related, in order to establish discriminant validity. The AVE is used for assessing discriminant validity, by comparing the square root of the AVE with the correlations among constructs. In this study, the square root of the AVE is greater than the correlation between the constructs [131]. These statistics suggest that each construct relates more strongly to its own measures than to measures of other constructs. The Heterotrait-Monotrait Ratio of Correlations (HTMT) is also commonly used as another option to assess the discriminant validity between two reflective constructs in the PLS-SEM model. After running the bootstrapping routine (5000 bootstrap samples in this case), all the coefficients in the study have a value below the recommended maximum value, which has been established at 0.9 between two reflective constructs.

4.2. Structural Model: Goodness of Fit Statistics

Absolute fit indices were included in PLS models [132]. These indices indicate how well a model fits the sample data [133]. Researchers should be very cautious when reporting and using model fit in PLS-SEM [127]. One of the most widely used is the standardized root mean square residual (SRMR). This is a goodness of fit measure for PLS-SEM that can be used to avoid model misspecification [132]. This index is defined as the difference between the observed correlation and the model implied correlation matrix. A value less than 0.08 is considered to indicate a good fit to the data [134]. For this model, the SRMR is 0.078, suggesting an acceptable model fit. The results of the model also suggest that the dimensions explain a large amount of variance in satisfaction, new image, and loyalty, with R2 values of 0.28, 0.26, and 0.20 respectively. The Stone–Geisser (Q2) results for the same variables are 0.20, 0.25, and 0.20 respectively, where values larger than zero indicate a good model’s predictive relevance.

4.3. Results of SEM

The conceptual model results (see Figure 3) show how both the cognitive and affective image influence image, which is a second-order construct. With a coefficient of 0.92, the results suggest that the cognitive image dimension has the most important positive influence on image. This situation is followed by the affective image dimension, which also influences image positively, although weakly (with a coefficient value of 0.18). The H11 and H12 hypotheses are therefore not rejected (

Table 6. Summary of hypothesis verification.

Hypothesis	Content	Verification
H1a	Cognitive image has a positive influence on image as a dimension	Supported
H1b	Affective image has a positive influence on image as a dimension	Supported
H2a	Image has a positive influence on satisfaction	Supported
H2b	Image has a positive influence on new image	Rejected
H3a	Satisfaction has a positive influence on new image	Supported
H3b	Satisfaction has a positive influence on loyalty	Supported
H4	New image has a positive influence on loyalty	Supported

).

Satisfaction and new image are strongly influenced by image, but the influence is only positive for satisfaction (0.53). New image is unexpectedly negatively influenced by image (−0.60). Given these values, hypothesis H21 is not rejected but H22 is rejected.

For the hypothesis that attempts to discover the relationship between satisfaction and new image and loyalty, it is very clear that the relationships are acceptable and positive, (with value coefficients of 0.30 and 0.35 respectively). Therefore H31 and H32 hypotheses are not rejected. Lastly, new image has a positive and significant influence on loyalty (0.28) and hypothesis H4 is not rejected.

Finally, it is appropriate to analyze the results of total effects (

Table 7. Total effects ¹.

	Loyalty	Image	New Image	Satisfaction
Cognitive image	0.07	0.91	−0.37	0.48
Affective image	0.01	0.18	−0.08	0.10
Image	0.08		−0.41	0.53
New image	0.28
Satisfaction	0.45		0.35

¹ Significant path coefficients (at p < 0.01).

). The total effect of satisfaction and loyalty shows an important influence (0.45). The influence of cognitive image on satisfaction should also be noted as the principal dimension that assists image in influencing satisfaction.

5. Discussion and Conclusions

5.1. Theoretical Implications

This research focuses on how tourism, and especially rural tourism, can be well-suited to developing the most under-populated areas of Spain [8]. To ensure that rural tourism has the desired effects, we must focus on the social and economic sustainability of this type of tourism, a tourism that should translate into improving the quality of life of the indigenous population of the area [18], and culturally and socially enriching the local community [19]. The social well-being of local economies is linked to tourism in those areas [25] and increases the sustainability of the local population [23,53,54,55,56,57], contributing to reducing poverty.

This social and economic sustainability of tourist areas can therefore only be achieved through increased visitor numbers, either due to an influx of new tourists or by gaining the loyalty of visitors who already know the area. Several authors directly link loyalty with future tourist behavior [109,110,111,112,113,114,115]. This loyalty, for Chon [121] is influenced, first, by the level of satisfaction that tourists experience as a result of the visit, and then by the new image that tourists create after the visit [114]. This new destination image—a modification of the initial image—should be positive [93], since that will create loyalty to the destination, increasing the number of visits to the area and increasing the economic sustainability of the area. Several authors, including Kastenholz et al. [89], Moliner et al. [135], Fandos and Puyuelo [136], Campón-Cerro et al. [137], Long and Nguyem [138], and Ryglová et al. [139] have studied the link between loyalty, increased visits to the area, and the consolidation of the development and sustainability of rural areas.

Therefore, to analyze the study of the sustainability of rural areas, we start from the previous image of the tourist area, the one that each of us has before the visit. This image is what attracts us to visit that destination. This destination image, which is made up of the affective image and the cognitive image [80,91], has a positive influence on satisfaction, but a negative influence on the formation of the new destination image [93]. The reason for this negative influence is because the worse the image visitors have of the province, the better the final image they have of the area [103]. Soria does not promote the province adequately, so the a priori image that potential tourists have of the province is not very good. However, on visiting the province this changes, and the final image is much better than the initial one. Satisfaction, as we can see in Figure 3, also has a positive influence on the new image of the destination [114,116], but its effect is less than that of the initial image. Both satisfaction and new destination image have a significant influence on loyalty, with satisfaction contributing the most to this variable.

In summary, it has been proven that the development of rural areas depends on the number of visits, and this is increased owing to the loyalty of tourists who not only repeat their visit, but also recommend the area to third parties. This loyalty is influenced both by satisfaction with the visit and by the new image that tourists take from the area.

5.2. Managerial Implications

From a managerial point of view, both for the different administrations and the owners of rural tourist accommodation and other establishments directly associated with tourism, achieving high levels of loyalty to the destination is very important. For the businesses involved in this sector, this social and economic sustainability is essential. The more visits they receive and the greater the loyalty to the destination, the higher the income they will obtain, and this can constitute a solution to the socio-economic problems of the most depopulated areas of the country [20,21,22].

The results we obtained from the survey of tourists staying in rural accommodation in Soria province show that destination image is a key variable for achieving that long-awaited loyalty. It acts both through the final destination image and through the satisfaction that the tourist feels when visiting the province, which is largely influenced by destination image [104]. This image must be heavily promoted by the local, regional, and national administrations so that potential tourists know more about the area since we have shown that the final destination image—the one that tourists have after the visit—is considerably better than the initial one. This indicates that Soria province has tourist potential that is not being promoted effectively. We have also seen (Figure 3) that the cognitive image has a much greater influence than the affective image when it comes to forming the final image. Therefore, these promotional activities are very important, as explained by Baloglu and McCleary [91] and Zhang et al. [80]. This image is principally formed as a result of the knowledge we obtain about the destination [93], rather than from the feelings that the destination causes in us.

5.3. Limitations and Future Research

The clearest limitation of this study is that we have focused on a single Spanish province—the province with the lowest number of inhabitants and a high degree of depopulation. This gives a general picture of what should be done in the most demographically depressed areas of the country, but it is limited to a single province. Future lines of research could extend the analysis to the rest of the Autonomous Community of Castile and Leon, of which the province of Soria is a part—and even to all of Spain, to obtain broader results. However, the model presented in this work could be the basis for future work, as it has proven to be very useful for this type of study.

Another future line of research would be to use the same questionnaire and method, but limit it to “loyal” tourists, i.e., those visitors who have already made a return visit to rural tourism accommodation in Soria province. This study should analyze, first, the extent to which the rural tourism offering conforms to sustainability practices. Second, it should evaluate the impact of tourist demand on the areas where such tourism is being developed—i.e., whether responsible consumption guidelines are being followed. For this, an exhaustive investigation could be carried out to verify that the promotion of rural tourism can be used to achieve the Sustainable Development Goals, especially Goals 12 and 14, and how these desirable outcomes can be ensured.

Finally, a similar study could be carried out by directing the questionnaire to tourists who focus on nature tourism, to discover any differences between them and rural tourists.

5.4. Conclusions

In summary, it has been proven that the development of rural areas depends on the number of visits, and that the number of visits increases as a result of the loyalty of tourists who not only repeat their visit but also recommend the area to third parties. It has also been shown that this loyalty is influenced both by satisfaction with the visit and by the new image that tourists take from the area.

All this demonstrates that, for the most depopulated areas of countries such as Spain, rural tourism is very important to meeting Sustainable Development Goal 8. That goal promotes inclusive and sustainable economic growth, employment, and decent work, which in turn drive progress and improve living standards. By implementing good rural tourism policies, as well as maintaining loyalty to the destination by promoting the tourist image of the area [10], the level of employment can be maintained in these areas, which will result in improved well-being for the local population [1].