Applying Social Networks in the Management of Sustainable Tourist Destinations: An Analysis of Spanish Tourist Destinations

Abstract

In this study, the presence and management of the social networks of 78 tourist destinations were analyzed for the development of sustainable tourism, with particular attention being paid to Spanish smart destinations. The variables for the empirical analysis were determined from a literature review, and it was concluded from a descriptive analysis, correlation analysis and an analysis of variance, that although the presence of tourist destinations on the internet and on social networks was notable, their management was inadequate for the development of sustainable tourist destinations. It was shown that there is a direct relationship between the number of visitors at a tourist destination and its presence on social networks. However, our analyses found that this correlation was not related to social network management; a greater number of visitors were not related to the effective management of social networks. It was concluded that smart destinations, despite having a technological advantage, did not stand out for their presence and management on social networks. The manuscript ends with some recommendations for the future

1. Introduction

Social networks (SNs) and the evolution of information communication technology (ICT) have changed the way we interact in almost all aspects of life. In fact, according to [1], by January 2018, 3196 million people (42% of the world population) were active users on SNs; specifically, in America 64% and in Europe 53% of the population were active SN users [2].

With this in mind, it is undeniable that SNs have expanded our horizons, the ways in which we socialize and, of course, the way that we purchase all kinds of products [3]. Moreover, SNs have reimagined the possibilities of tourism; tourism-based businesses have had no option but to evolve towards new methods of promoting their products using digital marketing [4].

The universe of SNs is unlimited; every day, new social networking options are born and others die. Therefore, maintaining validity in this digitally expanding world requires large quantities of dedication and research in an environment ruled by novelty; a social network may be in trend today, but could be replaced tomorrow by another more attractive and innovative edition [5].

New information and communication technologies play a key role in the development of tourist destinations, and have a considerable impact on the communication of their brand and identity [6]. Social media allows tourist destinations to interact directly with their different audiences, at a relatively low cost, at any time [7]. However, managing social media is not an easy task and requires new ways of thinking about communication [8].

According to [9], technology has changed the way in which tourists interact, as well as the activities performed before, during and after a trip. The use of SNs is not limited to sharing photos and following people; users also use SNs to seek information on new tourist destinations to be visited, travel offers and other activities focusing on the tourist experience [10].

There are many studies on the impact of social media on tourism, although not all offer the same information. Some authors highlight social media’s important role in the selection of tourist destinations [11,12], whereas others highlight that travelers have adopted collaborative tools such as blogs and microblogs, online communities, platforms to share videos or images and social bookmarking websites to search for information [13]. In short, all of this has created shifts in tourist profiles; through the development of ICTs, tourists are not only more informed, but their experience is broader, and they can design, plan and contract their own trips.

On the other hand, from the point of view of tourist destinations, SNs are viewed as bidirectional collaboration platforms, to develop cocreation processes between the destinations and the tourists themselves [14]. Additionally, according to [15], they allow for market research, monitoring, advertising, publicity and public relations regarding tourism demand.

However, the majority of internet users do not use the comments generated by consumers to organize their trips [16]. In this sense, [17] highlights that although social platforms have become a complementary source of information for tourists, other traditional sources continue to be a priority.

In fact, as stated by [18], although advances in ICTs are producing important access to tourist information, this information does not always belong to a service producer or a destination, but to a mainly virtual intermediary. Thus, the use of these tools becomes a challenge for the management of tourist destinations [19,20].

Not surprisingly, as authors continue to recognize, tourist destinations face a great challenge in the development of integrated technological systems that help to provide destination information in a dynamic and updated way. In addition to consolidating and distributing tourism products, these platforms could allow users to generate dynamic product packages, organize their own trips, or generate interactive catalogs, among many other utilities.

Taking these considerations into account, this study focuses on analyzing the degree of application of SNs in the management of tourist destinations, applied to Spanish tourist destinations, in general, and smart destinations, in particular.

To fulfill these objectives, the work is structured as follows. First, a theoretical framework is presented in which the relationships between tourism and SNs are collected, paying attention to the functionalities available for the management of destinations. Subsequently, a compilation of the research on tourist destinations and SNs in recent years is presented, to collect the main applications of SNs, and determine the variables to be used in the empirical study. The methodology used for the empirical analysis is explained and the results are presented, where the 26 destinations incorporated into the Smart Destinations Project of the Spanish government by SEGITTUR are analyzed, along with the 26 most visited Spanish destinations, and the 26 least visited. Finally, conclusions and recommendations are provided.

Theoretical Framework

Although there is no formal definition, social media can generally be understood as internet-based applications that carry consumer-generated content [21]. The content generated by social media includes a variety of new and emerging online information resources that are created, initiated and used by consumers with the aim of sharing information about products, brands and services [22].

From the moment it is considered that one of the functions of tourist destinations is promotion, it is impossible to conceive the execution of promotion without SNs [23]. In this sense, ICTs should not only facilitate the implementation of these social networks but also integrate with them [24].

Currently, an effective online communication strategy is considered a key element to achieve the necessary competitive advantages in the market and satisfy the information needs of current and potential tourists and attract new customers [19]. In addition, the content generated on the internet detailing the concerns of the users, can be used to improve the marketing of the destination, educate the consumers of tourist goods and services, and facilitate tourism transactions [25].

The participation and comments made by tourists on SNs involve descriptions of the tourist destination, its identity and its brand [26,27]. In the last ten years, we have witnessed the birth of new, increasingly independent and informed multichannel digital tourists, who require permanent connection to social media at all times as a basis for decision-making [28]. In addition, companies and destination managers must evolve from being “analog destinations” to “digital destinations”, to respond to these digital tourists before, during and after their journey [29].

ICTs have changed the rules of the game [27,30]; now, it is the tourists who self-plan, spread communication about, and evaluate the experience. Offers must be adapted to clients who require truthful information, the best value for money, authentic experiences and destinations that offer a unique tourist experience [5,31].

Promoting to tourists who find destinations through SNs has a high value, because SNs transmit the authenticity and freshness that new travelers seek, in addition to uncovering locations and experiences that can go unnoticed by residents, all at a residual cost for destination managers [32].

Due to the potential impact of social media on online tourism, understanding the role of SNs in the search for travel information is essential to improve marketing practices in the tourism sector [33,34].

SNs have revolutionized communication in general and tourist destinations are no exception [14,15,16,17,18,19,20,21,22,23,24,25,26,27]; the success of a destination is related to its incredibility in the SNs. According to [30], studies have shown that due to the uncertainty and risk involved in visiting unknown destinations, the comments and experiences of third parties provide credibility to users and potential tourists and influence their decisions in destination selection [15].

Moreover, [35] has shown that SNs provide important communication potential for locations and their brands, allowing the creation of dialog and relationships with the public [36,37]. Studies have shown that through conversations with users, SNs can help create images of destinations, allowing these destinations to be more easily identifiable. Thus, SNs create positive effects on user–brand relationships, which in turn leads to greater credibility and brand loyalty [38].

In addition, through SNs, tourists can share their travel experiences and emotions, directly influencing the emotions of other individuals on the network, and helping to create an image of the tourist destination in question [39,40].

In summary, studies that have analyzed the applicability of SNs to the management of tourist destinations have revealed the following functions:

(a)

SNs are a source of collaboration for the management of destinations through Web 2.0 environments, and provide tourists with an important ability to personalize their experience [41];

(b)

SNs offer personal and professional benefits related to learning, networking and personal reputation [42];

(c)

the possibility of using, enhancing and improving one’s creativity with a specific objective [17,43], and providing comprehensive and qualified information about the consumer while appreciating their changes in behavior and preference in real time.

The author of [44] classifies these functionalities into two large groups, pointing out that the integrated technological systems of destination management should be incorporated into SNs in two ways. Firstly, through content-dissemination functions, from the integrated system of the destination to the SNs themselves, and secondly, through content reception functions. The feedback that destination managers can receive from the comments of tourists on SNs can be extremely useful; the automated analysis of comments can be used as a basis for recommendation by the search engine of the integrated management system to generate highly personalized recommendations.

The author of [45] mentions that the emergence of social media has offered new opportunities and has been a substantial challenge for destination marketing organizations (DMOs) and the communication managers of tourist destinations who, in a short time, have had to adapt, and continue adapting, to this new reality of constant change [19,32,46]. Moreover, they have had to adapt to new communication styles and have progressed from simply allowing user comments to encouraging their participation [46]. This requires a change in mentality regarding communication, a recycling of human resources and the incorporation of communication professionals who specialize in social media [37,38,39,40,41,42,43,44,45,46,47].

Thus, regarding Spain for example, all the official websites of Spanish autonomous communities were engaged in at least one SN, as evidenced by the work of [12], in 2014. Among the most popular SNs at the time was Facebook, followed by Twitter and Tuenti.

Following these works—with the idea of updating their results—a bibliographic analysis was carried out on the theoretical studies that have analyzed the relationships between the management of tourist destinations and SNs in recent years, to highlight the contributions and functionalities in their management processes [48]. The result is shown in

Table 1. Studies on tourism and SNs.

Authors	Object of Study	Description/Contributions	Functions of the SNs
[1]	Examine the volume of information from SNs that influences the choice of smart tourism destination.	Influence of SNs on the choice of a tourist destination.	Recommendation
[2]	Analyze the different components of brand equity through the valuations of hotels in a community of travelers.	Valuations of brands through SNs used by travelers.	Knowledge of tourists
[4]	Analyze the intelligent experience and the intelligent destination.	Use of ICTs for the promotion of palaces as a smart tourism destination in cultural heritage management.	Promotion
[5]	To measure the influence of management responses to online consumer comments on subsequent comments.	Knowledge of digital leisure among international tourists from the perspective of a region of the world little researched.	Knowledge of tourists
[10]	To discover the places that most interest tourists and the routes they use most when visiting a tourist destination.	Analyze the routes tourists use most when visiting a tourist destination.	Knowledge of tourists
[24]	Discover the representative labels of a place through travelers’ logs and select the relevant and representative photos to visualize those labels.	Use of smart phones for functional and communication purposes for visitors.	Knowledge of tourists
[25]	To determine if the social distance between consumers and authors of comments influences a consumer’s response to what the author says.	Extract social vocations from the area, which are generally not easily quantifiable.	Recommendation
[39]	Analyze the need and effectiveness of smart tourism that offers information on travel in real time.	The application of smart phones and the satisfaction of users with respect to tourist information.	Promotion
[44]	Identify the influence of destination tweets on hotel reservations at the destination.	Improvement strategies for smart tourism destinations.	Promotion
[46]	Analysis of the online networks of tourist sites and offline groups of information seekers.	SNs as search engines for tourist information.	Information, offers
[49]	Identify the impact generated by users on business results.	Comments generated by users in SNs.	Recommendation
[50]	Detect implicit tourism preferences based on photos from SNs.	Tourism recommendation system that matches the attractions of the city with the profile of tourists.	Knowledge of tourists
[51]	Analyze the textual representations of the perceived image of a tourist destination found in travel blogs.	Images of a tourist destination through travel blogs.	Knowledge of tourists
[52]	Provide a method of significant growth and new stimulus to destinations.	Highlight the “potential” and “novelty” of tourist destinations.	Promotion

Source: elaborated by authors from bibliographic analysis.

.

From the previous table, it can be concluded that of the 14 studies consulted on the application of SNs by tourist destinations, most focus on analyzing the knowledge and profile of tourists (42.9%), followed by the promotion of destinations (28.6%) and their recommendation (21.4%). Finally, there is only one study that focuses on analyzing tourism offers presented on SNs (7.1%).

None of the studies consulted analyze the role that SNs can play in interacting with tourists and developing dynamic, cocreated tour packages. In effect, as [14] shows, tourist destinations do not configure cocreation spaces with key agents, especially tourists and companies in the sector who have a differential advantage, using the potential reference of SNs as an instrument of consumer inclusion in the development of new experiences. In this same sense, [12] concludes that there are interactions between the managers of the SNs of the communities and the private actors in very few cases of Spanish tourist destinations.

According to the latter authors, among the main weaknesses of the management of SNs by Spanish tourist destinations, the following are notable:

(a)

there are no workers trained and dedicated exclusively to the management of SNs;

(b)

no dialog is created, and the interventions are very impersonal;

(c)

there is only activity before the holidays of Christmas and Easter;

(d)

there is not much interaction with the home websites and SNs of the provinces;

(e)

no segmented interventions are performed;

(f)

they do not respond to the contributions and comments of the followers, therefore, there is no interactivity or dialog;

(g)

there is a great ignorance towards the potential of SNs on the part of professionals.

In short, from the analysis of the work on the management of SNs by tourist destinations, it can be concluded that although most destinations are present on SNs, seeking both to promote themselves and gain knowledge of tourists, they do not use the full potential of this digital marketing instrument. This is because proactivity, interrelation and daily dynamism and dialog with tourists through the SNs themselves are still practically nonexistent strategies for a good part of the analyzed tourist destinations.

The concepts of smart tourism and smart tourism destinations (STDs), have been gaining momentum internationally because of their potential to lead the way towards more sustainable developments (among other reasons). Social media has become an essential tool for channeling the interactions between providers and demanders of tourist services, producing an enormous data flow to feed the logic of smart tourism; where the two meet becomes a highly interesting subject of study. For tourist destinations, undoubtedly, this is a strategy that sets the scene for the future of this industry [9].

In this sense, it is interesting to focus on the application of smart destinations in Spain for several reasons [20]. Firstly, in arrivals as well as income from international tourism, Spain is situated in the top three tourist destination countries in the world. Secondly, Spain was one of the first countries to contemplate the project of smart destinations in its tourism policy; specifically, it was one of the measures included in the National and Integral Tourism Plan (NITP) 2012–2015, promoted by the Ministry of Tourism of the Spanish Government and managed by the State-Owned Company for the Management of Innovation and Tourism Technology (SEGITTUR) [53].

The smart destinations initiative was designed so that tourist destinations could successfully face the challenges and transformations posed by the new economic, social and technological environment worldwide, and the new connected tourist. Spain’s ‘Smart Destinations’ project, led by SEGITTUR, examined the effective use of digital technologies to develop the industry, at the same time as focusing on the sustainable development of a location by improving both the visitor experience and the quality of life for the local residents.

For these reasons, it is important to analyze the application of the ICTs in Spain’s ‘Smart Destinations’ and compare it with other Spanish tourist destinations.

2. Materials and Methods

To determine to what extent Spanish smart tourism destinations (STDs) use social media and networks, the official websites of the 26 tourist destinations that participate in the SEGITTUR project have been analyzed [53], as well as the 26 most visited Spanish tourist destinations, and the 26 least visited. Thus, we analyzed the internet presence and SN presence, as well as the type of management under which they operate, for each of these destinations, according to the variables defined below (

Table 2. Variables used by type of indicator.

Presence Indicator	Management Indicator
Ranking in the Google search engine	Updating the website
Number of social networks on which it is present	Dynamism
Number of followers on social networks	Proactivity
Number of publications on social networks	Interrelation

Source: elaborated by authors from bibliographic analysis.

). The data collection process was completed in May 2020.

According to the data from [53], the STD project sought a more efficient and sustainable management of the locations where tourism activity is based. STDs must guarantee the sustainable development of a tourist location, guarantee accessibility for all, facilitate the interaction and integration of visitors with the environment, and increase the quality of the experience at the destination, while improving the quality of life for the residents.

The concept of an intelligent tourist destination is defined as “an innovative tourist destination, consolidated on a state-of-the-art technological infrastructure that guarantees the sustainable development of the touristic territory, accessible to all, facilitates the interaction and integration of the visitor with the environment and increases the quality of an experience at a destination” [53]. Therefore, as this definition suggests, the presence of ICTs in the management of tourist destinations should be considered intelligent.

Indeed, the main axes on which to base all STDs are technology, sustainability (environmental, cultural and socioeconomic), information processing, knowledge generation and efficiency. However, as numerous studies conclude, the technological axis is experiencing the greatest degree of development [20]; hence, we considered in this study the degree of development in this axis, by the 26 Spanish tourist destinations that participated in the project. In this case, it was applied to the presence and management of SNs.

Thus, to determine the presence and type of management, the results for the 26 Spanish tourist destinations participating in the project were compared with those for the 26 most visited Spanish tourist destinations, as well as with those for the 26 least visited, to determine if there were significant differences between these groups. For this, according to the bibliography consulted, the following hypotheses were proposed:

 Hypotheses 1 (H1): 

In general, the management of tourist destinations through SNs does not obey a proactive and planned strategy integrated into a global destination strategy.

 Hypotheses 2 (H2): 

The degree of development of a tourist destination, measured by the number of visitors, helps to explain the presence and management of SNs. Thus, the greater the number of visitors, the greater the degree of presence and management of social media.

 Hypotheses 3 (H3): 

The relevance to the SEGITTUR project of STDs contributes to explaining significant differences in the presence and management of SNs. Thus, the conversion of a tourist destination to an STD should lead to a greater use of SNs in its management processes, because the technological dimension is one of the four dimensions on which the management of independent tourist destinations in the SEGITTUR project should be based.

Below, in the

Table 3. Tourist destinations.

Most Visited	Least Visited	STD
Calvià	Palafrugell	Almería
Palma de Mallorca	Santillana del Mar	Arona
Barcelona	Trujillo	Avilés
Granada	Benasque	Badajoz
Madrid	Cadaqués	Benidorm
Malaga	Barbate	Canal de Castilla
San Bartolomé de Tirajana	Ceuta	Castelldefels
Adeje	Sallent de Gállego	Donostia/San Sebastián
Seville	Ubeda	The Ejido
Valencia	Sanlucar de Barrameda	El Hierro
Zaragoza	Chipiona	Jack
Bilbao	Suances	The Val d’Aran
Torremolinos	Zafra	The Vila de Joiosa
Pajara	Lepe	Las Palmas de Gran Canaria
Cordoba	Arnuero	Leon
Santiago de Compostela	Vall de Boí (La)	Lloret de Mar
Alicante/Alacant	Arcos de la Frontera	Marbella
Salamanca	Ribadeo	Monfrague
Yaiza	Viveiro	Murcia
Mogan	Ribadesella	Noja
Toledo	Albarracín	Palma
Benalmadena	Cazorla	Puerto de la Cruz
Roqueta de Mar	Begur	Salou
Alcudia	Sigüenza	Santander
Fuengirola	Mazarron	Torrox
Sant Llorenç de Cardassar	Carboneras	Jerte Valley

Source: elaborated by authors from www.ine.es (accessed on 2 January 2021).

, are the destinations that follow the STD methodology in Spain [54], as well as the 26 most visited and 26 least visited destinations, according to [54], on which the empirical analysis of this research was carried out.

The analysis of the presence and management of these destinations on the internet and SNs was carried out according to the following process: the name of the tourist destination was inserted in the Google search engine; then, after visiting its website, the following variables, which have been used by the literature consulted for the analysis of the management of SNs in tourist destinations, were recorded [12,14,17]:

• Rank in the Google search engine: This variable represents the position in which the tourist destination appears in the search engine. The values are designated as 1 (first place), 2 (second place), 3 (third place) and so on.
• Year of Integration as an STD in the SEGITTUR project: This variable defines the year of incorporation into the project of STDs promoted by the Spanish government. The values that can be taken refer to the number of years that the destination has been in the SEGITTUR project (1, 2, 3, 4, etc.).
• STD website updates: This variable indicates the last time the website of the destination in question was updated, quantified as the number of days since its last update. The values that this variable can take are 1 (daily), 2 (weekly), 3 (monthly) and 4 (several times a year).
• Tourist activities most practiced at the STD (positioning): This variable allows knowing the type of tourist promotions offered by tourist destinations.
• SNs most used by the STD: This variable indicates the number and type of SNs that are most used by a tourist destination for promotion. The values that these variables can take are 1 (presence in 1 social network), 2 (presence in 2 SNs), 3 (presence in 3 SNs), etc.
• Number of followers on SNs: This variable indicates the number of followers currently on each social network for each of the destinations analyzed. The value is related to the number of followers.
• Number of STD publications on SNs: This variable quantifies the presence and activity of the destinations in each of the SNs in which they are present.
• Dynamism: This variable allows analyzing the type of contributions that the destination makes (daily, every week, before the holidays, etc.), whether dialog is created, and whether or not they invite participation and dialog. The values that can be taken are 1 (daily), 2 (every 2 days), 3 (weekly), 4 (very variable) and 5 (before vacation).
• Proactivity: This variable indicates whether the destination encourages participation in dialog or not. The values can be 1 (there is proactivity) and 2 (there is no proactivity).
• Interrelation with other websites of the destination (public administrations or private companies): This variable indicates whether interrelation among websites occurs. The values can be 1 (very much), 2 (some) and 3 (not at all).

In the following table, these variables are ordered according to the indicator they intend to measure: presence on the internet and SNs or related management of the internet and SNs.

The quantification of these variables for each of the 78 tourist destinations allowed us to detect the main characteristics of their presence on the internet and on SNs as well as the degree of use of these SNs in their management processes.

To contrast the first hypothesis, related to the degree of presence and management of the destinations in SNs, a descriptive analysis of each of the variables was developed. Subsequently, to fulfill the second hypothesis, Pearson correlation analysis was performed. This allowed us to establish the type of interrelation between the dependent variable (number of visitors) and the dependent variables, which referred to the presence and management of the destinations on websites and SNs. Finally, to contrast the third hypothesis and determine the degree to which STDs made use of SNs, ANOVA was performed between the variables of the most visited destinations and STDs to detect possible statistically significant differences among them.

3. Results

3.1. Descriptive Analysis of Destinations

Table 4. Frequencies.

Variable	Values	Percentages
Rank in the Google search engine	1	88.5
	2	7.7
	3	3.9
Number of social networks	1	1.3
	2	11.5
	3	17.9
	4	32.1
	5	24.4
	6	9.0
	7	1.3
	8	2.6
Website updates	Daily	84.6
	Weekly	5.1
	Monthly	5.1
	Few times a year	5.1
Dynamism	Dail	56.4
	Every 2 days	23.1
	Weekly	2.6
	Very variable	11.5
Interrelation	Very Much	28.2
	Some	50.0
	None	21.8
Proactivity	There is	44.9
	There is not	55.1

Source: elaborated by authors.

,

Table 5. Presence of social media in destination management.

Social Media	Number of Destinations	Frequency
Facebook	76	97.4
Twitter	77	98.7
Instagram	55	70.5
YouTube	55	70.5
Pinterest	18	23.1
LinkedIn	7	9
Flickr	16	20.5
WhatsApp	4	5.1
Google+	10	12.8

Source: elaborated by authors.

and

Table 6. Means and standard deviations.

Variable	Mean Value	Standard Deviation
Number of followers	65,568.18	119,600.537
Number of publications	1,104,186.53	4,552,791.516

Source: elaborated by authors.

show the values for the variables for the 78 tourist destinations analyzed. Table 4 shows the frequencies for: position on the web, number of SNs, website updates, dynamism, interrelation and proactivity. Table 5 shows the mean values, with their corresponding standard deviations, for number of followers and number of publications.

When entering the name of the destination in the Google search engine, as shown in Table 4, all occupied the first rank, except for Canal de Castilla, León, Fuengirola, Ceuta, and Suances, which ranked second, and Puerto de la Cruz, Lepe and Málaga, which ranked third. Therefore, 88.5% of the official websites of the analyzed tourist destinations were well positioned and, therefore, visible in the network, occupying the first place in regard to the outputs generated by the Google search engine. Regarding website updates, 84.6% of the destinations updated their websites daily; therefore, the data retrieved were indicative of their current status.

Almost 70% of the destinations analyzed were present on four or more SN platforms, and 87.3% were present on three or more. Therefore, it can also be concluded that the tourist destinations were present and used SNs in similar proportions to their presence on the internet.

Regarding the most used social media for this management, as shown in Table 5, the SNs Twitter and Facebook stood out with 98.7% and 97.8% of tourist destinations using these platforms, respectively. These SNs were followed by the presence on Instagram and YouTube, with 70.5% in both cases. Last, Pinterest (23.1%), Flickr (20.5%), Google+ (12.8%), LinkedIn (9%) and WhatsApp (5.1%) accounted for a minority presence.

However, when the management indicators of the SNs were analyzed, these proportions decreased substantially. Thus, compared to the daily website updates, only 56.4% of the destinations made daily contributions to SNs, thus reducing their dynamism. In addition, only 44.9% exhibited a certain proactivity, i.e., encouraging tourists to participate online. Finally, only 28.2% showed an interaction and interrelation with other websites relating to the destination, whether from other public administrations, entrepreneurs, etc.

Furthermore, as shown in Table 6, 59 destinations (75.6%) had less than the mean number of followers (65,568.18), and 67 (85.9%) had less than the mean number of publications (1,104,186.53), which was evident in the high standard deviation for both variables.

In short, when we looked at the presence of tourist destinations, both on the internet and on SNs, it could be said that in general terms their engagement was acceptable, and even important. However, when the variables and indicators related to the management of these SNs were analyzed, it was concluded that such management was not adequate; the percentage of destinations that relied on dynamism, interrelations with other agents and proactivity in networks decreased substantially, going from 80% to less than 50%. In fact, some variables, such as interrelations with other websites of the destination, barely reached 30%.

This led us to ratify the first hypothesis proposed in this research. The tourist destinations did not manage SNs in a strategic way, because despite being present, the management carried out presented certain deficits, with specific regard to proactivity and interrelations with other agents.

3.2. Number of Visitors and Behavior of the Destination on SNs

After describing the type of management that Spanish tourist destinations have been carrying out on SNs, this section analyzes the relationships that can be established between the degree of development of each destination and the dependent variable “number of visits”, regarding the independent variables that catalog the type of management on SNs. For this, correlation analysis, which is based on linear associations, is used; that is, when the values of one variable increases, the value of the other variable can increase or decrease proportionally.

There are two major types of correlation: Pearson and Spearman. Both are based on the same information, although they use different formulas. The Pearson correlation is more appropriate when the variables follow a normal distribution. The Spearman correlation is more convenient to use when the variables do not follow a normal distribution. However, in general, there are usually few differences between the results, which only vary when working with small samples. In this case, the Pearson correlation was calculated.

Table 7. Variable correlations.

		Number of visits	Number of SNs	Number of Followers	Number of Publications	Dynamism	Interre Lation	Proactivity
Number of visits	Pearson correlation	1	0.241 *	0.731 **	.732 **	−0.058	−0.127	−0.123
	Sig. (Bilateral)		0.033	0.000	0.000	0.616	0.269	0.281
	N	78	78	78	78	78	78	78

* The correlation is significant at the 0.05 level (bilateral). ** The correlation is significant at the 0.01 level (bilateral). Source: elaborated by authors from SPSS.

shows a correlation between the dependent variable “number of visits” and the independent variables related to the presence and management of SNs (number of SNs, number of followers, number of publications, dynamism, interrelation and proactivity). In this sense, for the presence on SN platforms, the number of followers and the number of publications was positively related to the number of visitors to tourist destinations, as the significance value was less than 0.05. However, when the variables related to the management of SNs were analyzed, it could be concluded that there was no correlation between these and the number of visitors, because the significance value for the three variables was greater than 0.05.

In short, with a presence on SN platforms, as well as followers of and publications to those networks, the most visited tourist destinations acquired higher values; however, the management of those SNs in which they were present was not the most appropriate, because the variables of dynamism, interrelation and proactivity had values higher than the bilateral significance of 0.05.

The correlations between the number of visitors and the presence on SN platforms, through the number of SNs where it was present, the number of publications and the number of followers, can be seen in Figure 1. The absence of a correlation between the number of visitors and the management of SNs, through dynamism, interrelationships and proactivity, is shown in Figure 2.

In short, this correlation analysis shows how Spanish tourist destinations, in general—and the most visited, in particular—despite being present on SNs do not perform at a suitable level of management. That is, we found that the degree of daily intervention, the proactive nature and the invitation to tourists to participate, as well as their interrelationships and dialog with other agents at the destination and with the tourists themselves, did not exceed half of the destinations studied. This last indicator was met by only 30% of the 78 destinations analyzed.

This led us to partially refute the second hypothesis; it was stated that there was an important degree of positive correlation between the number of visitors to the destinations and their presence on SNs. However, it was concluded that this correlation was nonexistent when the dependent variable (number of visitors) was related to the independent variables that measured the type of management of SNs for tourist destinations. Thus, it cannot be said that the most visited destinations managed SNs more efficiently.

3.3. Behavior of STDs with Respect to the Most Visited Destinations

Finally, the behavior of Spanish STDs on SNs compared to the most visited Spanish tourist destinations was analyzed to demonstrate whether the integration of destinations in the SEGITTUR project, i.e., the transformation into smart destinations, could be associated with a greater presence and management of SNs with respect to the most visited destinations. To do this, in order to detect if there were significant differences between the two types of destination regarding the presence on and management of SNs, ANOVA was performed.

Table 8. Descriptive statistics of the variables analyzed.

		N	Mean	Std. Deviation	95% Confidence Interval for the Mean
					Lower Limit	Upper Limit
Internet activity	STD	26	1.42	0.945	1.04	1.80
	Most visited	26	1.08	0.272	0.97	1.19
	Total	52	1.25	0.711	1.05	1.45
Number of SNs	STD	26	4.15	1.690	3.47	4.84
	Most visited	26	4.58	1.238	4.08	5.08
	Total	52	4.37	1.482	3.95	4.78
Number of followers	STD	26	81,796.31	88,430.685	46,078.38	117,514.23
	Most visited	26	103,901.23	176,786.236	32,495.72	175,306.74
	Total	52	92,848.77	138,845.812	54,193.85	131,503.69
Number of publications	STD	26	406,843.54	816,993.905	76,852.56	736,834.52
	Most visited	26	2,834,863.15	7,644,343.927	252,754.18	5,922,480.49
	Total	52	1,620,853.35	5,520,417.465	83,959.31	3,157,747.38
Dynamism	STD	26	2.08	1.547	1.45	2.70
	Most visited	26	2.04	1.483	1.44	2.64
	Total	52	2.06	1.501	1.64	2.48
Interrelation	STD	26	2.04	0.774	1.73	2.35
	Most visited	26	2.08	0.796	1.76	2.40
	Total	52	2.06	0.777	1.84	2.27
Proactivity	STD	26	1.50	0.510	1.29	1.71
	Most visited	26	1.50	0.510	1.29	1.71
	Total	52	1.50	0.505	1.36	1.64

Source: created by the authors based on SPSS.

shows the mean values for these variables for each of the groups, whereas

Table 9. Robust tests of equality of means.

		Statistical a	gl1	gl2	Sig.
Internet Presence	Welch	3.219	1	29.103	0.083
Number of SNs	Welch	1.060	1	45.844	0.309
Number of followers	Welch	0.325	1	36.774	0.572
Number of publications	Welch	2.593	1	25.571	0.120
Dynamism	Welch	0.008	1	49.910	0.927
Interrelation	Welch	0.031	1	49.959	0.860
Proactivity	Welch	0.000	1	50.000	1.000

^a sAymptotically distributed function. Source: created by the authors based on SPSS.

shows the Welch test results of the ANOVA.

As shown in Table 9, the Welch test yielded nonsignificant results (p > 0.05) for all the variables considered. This implied the absence of statistically significant differences between the mean values taken by the variables for the two types of destinations considered, both those related to the presence on SNs (number of SNs on which they were present, number of publications and number of followers) and to the management of websites and SNs (updated website, dynamism, interrelation and proactivity).

The significance values for each of the variables can be observed in Table 9. It was concluded that the variables that most approximated the possibility of statistically significant differences between destinations (Sig. > 0.05) were those related to presence on SNs (number of publications, number of SNs on which destinations were present and number of followers). These possible differences, without being statistically significant, favored a greater presence on the SNs of the most visited Spanish tourist destinations.

Therefore, based on the ANOVA results, the third hypothesis can be rejected. STDs, despite being integrated into the SEGUITUR project, did not have a greater presence on SNs, and their management did not differ from that of the 28 most visited tourist destinations in Spain. Therefore, despite being one of the most developed technological dimensions in the transition of tourist destinations to smart-tourism-destination models, destinations are not taking advantage of the important opportunities that SNs confer for their management, especially with regard to promoting dialog with agents in the sector and enabling tourists to cocreate experiences and sector demands.

4. Conclusions

This research aimed to highlight the applications that SNs can have as management tools for tourist destinations, and identify those tools that are currently most used by the destinations themselves, paying special attention to Spanish tourist destinations in general and smart destinations in particular.

Thus, the analysis of the literature highlighted the important potential that SNs have for the management of destinations, as well as the challenges they present, to improve their competitive advantage. This requires a change in mentality regarding communication, a recycling of human resources and the incorporation of communication professionals who specialize in social media [29,37,48].

According to the consulted literature, the main functions that SNs can have for destination management include the following:

(a)

a source of collaboration for destination management through Web 2.0 environments, which provides tourists with an important ability to personalize and cocreate their experiences [42];

(b)

personal and professional benefits related to learning, networking and personal reputation [43];

(c)

the possibility of segmenting and using, enhancing and improving one’s creativity with specific management objectives [17,44];

(d)

providing exhaustive and qualified information regarding consumers while allowing observation of changes in behavior and preferences in real time [55].

However, the studies carried out in this regard showed that the main functions currently performed by SNs in the management of the tourist destinations were fundamentally reduced to dissemination and promotion as well as for the knowledge of the opinions and behavior of tourists.

In this study, focused on the analysis, presence, and management of SNs by Spanish tourist destinations, the results coincided with those of authors such as [12,14,17], who affirmed that the main function of SNs for tourist destinations is promotion, and gaining knowledge regarding tourists, and that they lack (a) active management strategies to interact with other agents at the destination and (b) participation and dialog with tourists.

In this sense, according to the results of this research, we concluded that for the Spanish tourist destinations analyzed, despite being present and visible on SNs, their management of SNs was inappropriate, presenting serious deficits regarding proactivity, dynamism, interrelation and dialog with different agents in the sector, both those located at the destinations themselves and with tourists.

Thus, as [12] concludes, practically 100% of the destinations analyzed were present on some form of SN, with Facebook, followed by Twitter, being the most used SNs by tourist destinations.

Although the most visited Spanish tourist destinations had a greater presence on the internet and social media, showing a direct correlation between these variables, this did not imply that they managed their SNs effectively. Therefore, for the main Spanish tourist destinations, the management of SNs was not ideal, because they are not used to interacting with the tourists and creating tourist products. They are using SNs purely to promote the destination and to gain knowledge regarding the opinions of tourists.

Finally, the Spanish tourist destinations that have been integrated into the SEGITTUR project and that are therefore moving towards STDs, have not been managing SNs in an efficient way, even though their technological dimensions were the most developed in this project. This demonstrated, once again, how neither the most visited tourist destinations nor STDs have been exploiting the competitive advantage derived from the efficient management of SNs.

Therefore, we recommend that tourist destinations, mainly those STDs integrated in the SEGITTUR project, use new technologies as management tools and implement a decided strategy of professionalization for SN management.

Not surprisingly, tourist destinations must be present and actively participate on these media platforms and SNs because—in addition to the interaction with users—they allow interactivity between supply and demand, as well as the creation of innovative marketing strategies. Thus, when the latter are creative, well planned and used together, they can increase the number of users, achieve greater visibility and create a great competitive differential for tourist destinations, at a very low cost.

For all of these reasons, tourist destinations in general, and Spanish tourist destinations in particular, both the most visited and those in the SEGITTUR project as intelligent tourist destinations, must decisively take advantage of the important potential that SNs have for their management. This recommendation is important both due to the progressive development of new technologies and the evolution of the behavior and profile of tourists, who expect greater tourism experiences with each visit, are more familiar with the use of new technologies, and demand flexible experiences adapted to their preferences, among other characteristics.

In this sense, it is recommended that tourist destinations have a content manager for social networks, to improve the interaction with tourists and analyze demand, among other functions. This could contribute to improving the quality of the experience offered at tourist destinations.