The Value of Cluster Association for Digital Marketing in Tourism Regional Development

Abstract

This paper analyses the advantages of membership in a cluster in the effective use of digital marketing tools and in a general way, in the performance, especially for the small and medium firms in underdeveloped regions. For this purpose, a case method research was conducted in the tourism sector, specifically in the hotels in the La Guajira Department, Colombia, where there is a regional tourism cluster. The tourism sector especially depends on digital marketing and the proper use of available digital marketing tools play an essential role in the performance. To conduct the study, 40 hotels in La Guajira were analyzed, whether or not they were members in the cluster. The obtained data were assessed by means of fuzzy set Qualitative Comparative Analysis to check the hypotheses. The results reveal the most effective combinations of digital marketing tools and the activities in which especially small and medium firms must engage in the cluster to obtain better results.

1. Introduction

Tourism is one of the most relevant activities for the development of regions and represents a major percentage of the wealth generated in the world [1]. To create a successful tourism destination is complex. Tourism requires the perfect combination of at least three major areas of activity [2]: accommodation, restaurants and transport. These three services are carried out by different actors that hinder the planning and marketing coordination. In these cases, the creation of regional clusters that foster the joint development of tourism destinations can be a successful tool [3,4]. At the same time, digital marketing is paramount in the success of tourism firms in particular and destinations in general [5,6]. Despite the importance in tourism of these two elements, clusters and digital marketing, there are not many studies about how membership in a cluster is a dynamic factor in the use of digital marketing and the same time, how much the synergy of the two elements help to develop a tourist region [7,8] especially if the sector is comprised by small firms with low economic strength, size and experience.

During recent years, digital instruments have been developed which have permitted obtaining competitive advantages in the market, where digital marketing has become the dominant media in the tourism sector [9]. The digital marketing tools include the consumer in all the planning and development of the marketing process, demonstrating greater effectiveness than traditional tools.

The digital marketing tools have already celebrated a decade of full development with a significant and growing investment in companies, which have shown annual growth rates of approximately 26% [10]. One of the industries with the greatest positive impact on the productivity and effectiveness in sales due to the proper use of digital marketing tools is tourism. For example, in the USA, around two-thirds of the population carry out searches for trips and tourism by means of digital media [11] and over 74% of the travelers base their search preferences and their choices for their travel plans, on the user comments in the digital media [12].

Despite the importance of digital marketing in tourism, there are very few tourism companies with a small size in underdeveloped regions which have the capacity, vision and know-how to implement it in an effective way.

This article analyses how the proper use of digital media has an impact on companies which belong to the tourism sector in the Colombian department (region) of “La Guajira,” a business in which digitalization is strictly necessary in order to compete. The objective of these media platforms is to satisfy the needs and expectations of customers, who seek to carry out their purchase and reservation processes in a digital way [13]. For this purpose, a study and classification of the digital marketing tools have been performed, reviewing their use and impact on the tourism sector. Their aim is to analyze how the use level of the digital tools has an impact on brand creation, the competitiveness and productivity of the companies that belong to the tourism cluster in the Colombian La Guajira region. Likewise, it reviews if membership in this cluster has an added-value in relation to the use and benefit of the digital tools in the tourism market in this area of Colombia. The analysis of how the affiliation to the regional cluster affects the hotel performance and how effectively the digital marketing tools are used is carried out by means of case study research [14] in combination with fuzzy set Qualitative Comparative Analysis (fsQCA).

2. Theoretical Framework

2.1. Clusters in the Tourism Sector

The theory defines the term cluster as a geographic concentration of interconnected companies, specialized suppliers and customers as well as associated institutions [15]. The organized concentration of companies generates entry advantages such as facilitating the access to specialized labor and specialized services [16]. Membership in a cluster helps companies to rely on a broader and more accurate perspective of the market in comparison with competitor companies which operate outside them. The operation as a cluster permits the handling of a greater volume of technical information [17] of the market and the competitors. This makes it possible to generate benefits for the cluster’s participants since they have a unique or preferential access to the information, hence ensuring the trust among the member companies and enhancing the personal links of the employees and management staff.

The tourism companies are developed thanks to the opportunity provided by certain localizations in order to create tourist experiences. Consequently, the tourism clusters are the result of the interaction and the cooperation of companies in this industry in a specific destination [18]. The researchers have conducted an in-depth study of the benefits of tourism clusters in the economy of the regions where said clusters are developed [19], jointly with productive improvements and competitiveness in the region [3].

On the one hand, there are a few studies in digital marketing in hotel clusters, on the other hand the performance of the tourism clusters has been an academic topic of extensive study from the perspective of industrial cluster, studying its impact on the regional economy and the hotel-restaurant performance [20] likewise, the strategic creation of hotels in tourist areas under specific patterns directly contributes to the competitiveness [21]. The tourism companies can be developed through business clusters, in which the cooperative and competitive interaction of the local tourism companies, the support industries and businesses, jointly with the remaining related industries, discover more incentives for innovation and differentiation [3].

2.2. The Clusters and Innovation

There is extensive literature about the industrial clusters due to their geographic location and the consequences which they have on innovation [22]. However, there is little literature about how membership in a cluster helps small firms and recently created businesses to innovate and develop their brand

Innovation can result from the constant pressure from the competition, from peers, from the comparison and the adoption of the best practices in the production and the product or service, regardless if it is in the quality, cost, flexibility or delivery time. The formation of a cluster represents an increase in the information exchange between companies, individuals and institutions inside the cluster, generating environments where creativity and innovation are developed [23]. This has been reflected in the fact that the integration of companies in different industrial sectors at the regional level has a positive relation with the activities of innovation and employment [24]. Besides the regions with a higher volume of clusters developed in different sectors and industries have a positive trend in the research and development (R&D) investments [24].

Despite its importance the adoption of tools and practices in digital marketing still represents a radical innovation for many companies from underdeveloped regions, especially small firms, since the companies with a bigger size have higher R&D indicators than the small firms [25] in the use of information technologies [26]. When small tourism firms in a region depend on the development of the destination image for their survival, they need to cooperate to join efforts. The actions on digital marketing are a powerful tool in tourism and they are a potential objective to develop in tourism clusters.

2.3. Digital Tools as an Instrument for the Development of Tourism

Digital marketing permits the communication of corporate information in an economic way and reduced time periods and in turn, permits obtaining information from the user opinions about the provided products and services. In the tourism industry in general and the hotel sector in particular, the proper use of digital marketing and its tools permit the hotel managers to know and track the attitudes, opinions and satisfaction of the clients [25], which helps the management in the provision of services. If the hotel managers assign a value to the comments and opinions of their users, the probability increases to improve the way in which the consumers of the service perceive the quality of the hotels [27].

Due to the competition among the provider companies of tourist services, it is continually necessary to improve the quality of the service. First-hand knowledge of the user opinions is essential and this is where the social networks play a major role by identifying the opportunities to improve the service [28]. Likewise, through these social networks, the users communicate to the other potential customers what the tourist company needs to know in order to position itself. It is mandatory for hotels, restaurants or any tourist company in general to resort to active listening [29], actively participating in the management of the service and the on-line customer service [30]. Consequently, the digital tools are a major source in order to reach the customers in an effective way.

Nowadays, thanks to digital tools, the users can obtain relevant information about the products and services offered by the different companies in the Internet. By means of the contributions from the users of different digital platforms, this has facilitated the interaction between the interested parties and the decision-making process of the purchase [31]. These types of interactions have become a challenge for the organizations in the tourism sector (hotels, restaurants, travel and leisure firms), since they must face a major volume of positive and negative comments [32]. The investigations reveal that the interactions and comments about the products or services have so much influence on the purchase decision that it is possible to duplicate frequency in the selection of products if they are recommended by other users. Their influence also depends on the source of those who recommend them and their social recognition [32]. Another source of valuable information at the time of making a purchase decision or selecting a service are the qualifications, which are the second most reliable source of information about the brand, followed by the recommendations from family members and the social circles of the user [33]. According to this, digital marketing relies on high flexibility to measure the results in comparison with traditional marketing. Likewise, the high profitability generated by these tools and the customer trends towards their constant use mean that investing in digital marketing is very interesting for companies [34].

2.4. The Tourism Clusters and Digital Marketing

The effects of membership in a cluster on the performance in general have been extensively studied. One of the most important factors for evaluation of the clusters is the productivity, which plays a very important role and reveals that the companies which integrate it show significant improvements in the obtainment of raw materials and inputs, technology, innovation and the coordination with companies which integrate the cluster [35]. Companies in a cluster can modify too the way they assume the new challenges when faced with the need for improvements. Several studies have demonstrated that the hotel clusters have a direct influence on the performance of their member companies, with a repercussion on the effectiveness and their positioning in the market, in turn, improving the scenarios of economic survival [36]. On the other hand, other researchers have found that there may also be negative effects, not just positive ones and that both can occur in a simultaneous way [37]. Likewise, their effects may vary among industries [38]. For the case of tourism clusters in a specific region, the studies show that they have a significant impact on the economic performance of the cluster companies in a positive way [39], particularly in the companies with a small size. Specifically, for hotels, the research on clusters have demonstrated that the performance of the low cost hotels which are located in the same cluster platform with high cost hotels is much higher than the hotels that do not belong to the cluster and work on a separate basis [40].

Despite the interest shown by researchers on tourism clusters, the number of academic papers that analyses the effect of membership in tourism clusters on the effectiveness of the digital marketing is more limited, despite the fact that numerous studies have identified the importance of digital marketing at the time of selecting a hotel or accommodation by the tourists, who rely on many choice options and destinations due to the major offer of digital platforms [41].

Today, the use of social media through the Internet has revolutionized the relation between the customer and supplier [42,43]. The companies receive feedback about their services from the digital media, expressed in likes, comments, shared contents and qualifications in social networks. In relation to social networks—Facebook, Instagram and WhatsApp, they are the most attractive due to their quantity of users [44] and hence, they are being used for brand creation in different industries, with special relevance in the tourism sector. For example, Facebook is considered to be a vital social network to generate engagement [45]. Small tourism firms use these less expensive platforms to increase the demand for their services and enhance their presence in the digital market [46], in addition, these platforms generate a sensation of authenticity [47]. There are various studies which analyze the decisions to select the hotel by digital platform, considering the reputation, comments on the cleanliness, staff friendliness, price, comfort and safety/security [48].

Considering the importance of digital marketing in the tourism sector, essential issues which this study aims to answer are expressed in the form of the hypotheses below:

Hypothesis 1 (H1).

The performance of the tourism companies has a strong dependence on the proper and strategic use of digital marketing tools.

However, not all the companies have the capacity and skill to use digital marketing in a strategic way, especially the small size firms where the managers do not possess the skills required to implement the suitable tools. In these cases, membership in a cluster can favor the development of this strategic vision by the management and equip the companies with the capacity and expert advice for the implementation of digital marketing.

But, how the cluster membership can help to develop the digital marketing skills and shape the manager’s vision on digital marketing, especially in small firms where are no specialized managers on social networks tools? Regarding managerial skills on digital marketing, they are the abilities that let to coordinate digital marketing activities and to work with marketing consultants, information technology (IT) professionals and customer in developing digital marketing initiatives. The managerial skills are mostly tacit [49], intertwined with personal relationships. This tacit knowledge is gained over time by trial and error, working and experiencing the use of digital marketing tools. The friendship, trust and interpersonal communication necessary between IT professionals and business managers to exploit novel digital marketing tools are socially complex. The “share knowledge” culture between IT professionals and business managers to leverage the potential of IT in general [50] and digital marketing tools in particular, is essential for a strategic use of these technologies. The technical knowledge, when combined with an in-depth knowledge of the business and its processes and activities, permits to exploit the potential of digital tools and fulfill the needs of hotels in customer’s relationship management [51].

The participation in courses on digital tools promoted by the cluster management and a strait collaboration with other hotels in the cluster with larger experience on digital marketing can afford to small hotel managers the vision of the potential of digital marketing and the knowledge of trustable IT professionals. General managers’ competences such as leadership skills [52] and business vision influence all the resources allocation and capabilities development of the organization, including digital marketing skills. Besides, the knowledge of digital marketing professional with experience on hotel activities is paramount. The importance of the IT professionals derives not only from their technical skills but from their knowledge of the organizations and its processes and activities and from their interpersonal abilities and management knowledge in developing a strong IT-business partnership [53]. Besides, in some cases the business knowledge can only be gained through working experience with business people, making it tacit and difficult to transmit. Consequently:

Hypothesis 2 (H2).

Membership in a cluster favors the innovation and strategic use of digital marketing, especially in the companies which have lower economic strength, size and experience in a cluster.

These hypotheses are the assumptions that guided the study and let us answer other related questions such as which are the most effective combinations of digital marketing tools for hotels; which are the performance dimensions most influenced by digital marketing?; how much can cluster membership help to develop digital marketing competences in small hotels in underdeveloped regions?; And what kind of participation for a hotel inside the cluster is the best to improve its digital marketing competences?

3. Methodology

3.1. Procedure and Sample

To verify the work hypothesis, a tourism cluster was analyzed in a zone with tourist potential but still in the development phase. The objective was to perform an in-depth analysis of the companies that compose the cluster and compare their operation in terms of digital marketing with companies outside the cluster, so a specific database was created to study 40 hotels. Because our goal was theory refinement as well as theory testing, cross-case analysis was carried out using fuzzy-set qualitative comparative analysis (fsQCA) [54]. Although correct use of QCA depends on the ratio of cases to causal conditions, 30 cases is considered sufficient for reliability in this method [55].

The research was carried out between December 2019 and April 2020 in La Guajira Department in Colombia. For this purpose, 20 hotel companies were analyzed registered in the tourism cluster of middle and upper Guajira and an additional 20 hotel companies were analyzed in the same department that do not belong to the cluster.

The La Guajira cluster was created by the national government of Colombia with the objective to develop different innovation processes which would redefine the perspective of the companies, focused on a very demanding international market, in turn, managing to identify new needs of the market. There was a desire to qualify and establish collaboration networks so that the employers of the region could create an attractive tourist destination and in turn, facilitate a more accelerated development of the region.

On the other hand, it must be taken into account that this region is unique in Colombia, since 80% of its population are comprised by one of the country’s most representative indigenous ethnic groups—the “Wayuú” tribe, which has made this destination into a magical place to discover, according to the employers interviewed in this study.

For the Economic Studies Office of the Ministry of Trade, Industry and Tourism of Colombia, La Guajira Department features indicators are shown in

Table 1. Tourism indicators of “La Guajira.” region.

Indicator	2018	2019
Area approved under the building permit with a hotel destination (m2)	413	2137
Visitors of natural national parks (people)	18,252	19,134
Foreign non-resident visitors (people)	2248	3015
National airline passengers	82,225	123,221
International airline passengers	1197	3340

:

According to the Ministry of Trade, Industry and Tourism of Colombia, in recent years (from 2016 to 2019), in La Guajira Department, 657 hotel rooms were built and 216 were remodeled, with an investment of 43,753,000,000 Colombian pesos. In Riohacha (the Capital city of the La Guajira Department), 361 rooms were built and 179 were remodeled, with an investment of 12,293,000,000 Colombian pesos. The above data illustrates the importance which this region has for the economic development of La Guajira Department.

The hotels which were included in this study have a 1 to 5-star classification; note that these classifications were not the basis for their selection. The hotels for this study were selected due to the economic impact which they have in the region according to La Guajira Chamber of Commerce director and in each municipality where they are located, jointly with their membership in the cluster. The total number of municipalities where these hotels are located amount to 15. The average operating time of the surveyed hotels amounts to 10.8 years with an average of 18 rooms in every hotel.

24 variables were evaluated. The first group of 5 variables are related to the cluster: membership in the cluster, years in the cluster, collaboration with other hotels of the cluster, degree of participation in the activities promoted by the cluster, situation in the cluster network. The following variables measured the use of 10 tools for traditional marketing: web site, use of digital platforms different from the traditional social networks to promote their products and/or services. (Booking, on-line directories, Trivago, among others), the degree of use of blogs, Facebook, Instagram, e-mailing, google AdWords, YouTube AdWords, LinkedIn and Twitter. Finally, 7 variables of performance were analyzed: brand image in Internet, brand image evaluated by the competitors, growth, use of the capacity, profit, return on investment in digital marketing (social networks, digital platforms of hotels, directories, among others). Likewise, three variables of basic control were added: age of the company (years), size (number of rooms) and hotel category (in stars).

For the development of this study in December 2019, visits were carried out to 40 hotel companies located in La Guajira Department with the collaboration from the regional Chamber of Commerce. The legal representatives and managers from the different hotels were contacted with whom the study was going to conducted. The hotel selections were made based on the recommendation of the Chamber of Commerce of La Guajira. During the months from January to June 2020, surveys were carried out by digital media such as Zoom, Skype, Teams WhatsApp video, to each one of the legal representatives of the different hotels, who, thanks to the collaboration from the cluster’s management, were very receptive when performing the investigation.

3.2. Measurements

The independent variables were evaluated in the following way. Several of them, such as the dichotomy of membership in the cluster or the number of years in the cluster do not represent any problem. For other variables, it was necessary to establish the criteria for their evaluation and subsequently verify their validity in a subjective way. Hence for the situation in the cluster network: the scale was established as the number of cluster companies with which the hotel has frequent relations. Other aspects required the Likert scale, such as the degree of participation in the cluster, directly asking the management. For the variables measured with the Likert scale, a 7-point scale, from 1 (very low) to 7 (very high) was always used.

For the evaluation of the digital marketing variables, we considered the most relevant tools according to Cizmeci and Ercan [9] and created an objective scale. It was necessary to establish several subjective evaluation criteria for each tool, although once these criteria were fixed, the individual evaluation of the specific tool was objective. For the evaluation of the “Web site,” the following items were considered with a 0/1 value which were added to provide the final score: it does not have a web site, (it is not possible to acquire additional score), it has security Secure Sockets Layer (SSL), it is equipped with a common chat/WhatsApp Chat, on-line room reservations, multi-language translator, Secure Online Payments (SOE) payment channel and finally, it is responsive for cell phones, the maximum score for this variable is 7.

For the variable: “it uses digital platforms” different from the traditional social networks in order to promote their products and/or services. (Booking, on-line directories, Trivago, among others), the following evaluation was used: a 1 was added for each platform used, such as Trivago, Booking, on-line directories, www.olx.com.co, groups in Facebook (market places), Google my business and others. The sum total is the variable score.

The Blogs variable was evaluated by the number of monthly updates carried out in the blog. Hence for example, an average of monthly updates between 3 and below 4 per month would have a score of 3 in the scale.

The Facebook variable was evaluated by the sum of the following items with a 0 or 1 value: it has a fan page (more points cannot be added in a negative case), it makes more than 1 daily publication in its fan page, it makes at least one advertising page per month in its fan page, it uses the services scheduling option of the fan page, it has the Facebook pixel linked to its web site, it makes posts in specialized groups of sales and services at least once per week, it carries out the analytics for all its campaigns in Facebook, it performs some type of management to increase their followers in Facebook.

In reference to the Instagram variable, the following items were also evaluated with a 0 or 1 value, to subsequently calculate the sum: it has a corporate Instagram, it has completed other contact elements (e-mail, telephone numbers, address, website), it has linked the Instagram account with its fan page in Facebook, it makes at least one publication per day, it makes at least one advertising payment per month in Instagram, it makes at least one daily publication in the histories to promote its services or products, it uploads at least one professional advertising video to its feed and histories per month.

The same methodology was used for the e-mailing item, which evaluated the following items: it performs campaigns, it carries out campaigns with a landing page for the management of the e-mail database, it performs one campaign per month, it carries out 2 campaigns per month, it carries out campaigns by sending promotional e-mails to more than 100 users, it carries out segmentation for each campaign, the campaigns contain links to make the Booking in the hotel, it has a Premium account which permits sending over 10,000 e-mails.

The Google AdWords variable was evaluated with a 7 point Likert scale in the following way: a score of 1 if it does not carry out campaigns, a score of 2 if it carries out at least one campaign per month, a score of 3 if it carries out two campaigns per month and successively up to a score of 7 if it carries out 6 campaigns per month or more.

In relation to the YouTube AdWords variable, it was also evaluated in a similar way with a 7 point Likert scale in the following way: A score of 1 if it does not have YouTube channel, a score of 2 if it has a channel, a score of 3 if it carries out at least one campaign per month, a score of 4 if it performs at least two campaigns per month and hence successively up to score of 7 if it carries out 5 or more campaigns per month.

For the LinkedIn variable, the sum was carried out for each one of the following positive items: It has LinkedIn, it has a non-corporate LinkedIn, it has a corporate LinkedIn, its employees have LinkedIn where they relate with their company, it makes at least one publication per day, it performs some connection management process (followers), it makes at least 1 advertising payment per month.

The same methodology was applied for the “Twitter” variable, which has the following items: it has an account with a non-business Twitter, it has a Business Twitter, it generates a post in the business account to generate traffic to its web site, it carries out monitoring of relevant news stories for its business, it uses its corporate Twitter account to provide information to its customers, it organizes and analyses events for its Twitter account, it has private lists of its competition in order to analyze their campaigns, it has private lists for people classification (customers) in a group.

In relation to the performance variables, they were measured by means of three classic financial indicators that have been extensively adopted in the literature: return on investment, profit and sales growth [56]. We added to the digital marketing return as an specific ROI. In addition, we use two brand image indicators, brand image in the Internet [57] and brand image perceived by competitors.

The “brand image in Internet” was operationalized by the sum of the following items which take a 0 or 1 value: greater quantity of positive comments in the hotel digital platforms used and social networks than the negative comments, hotel classification in the different hotel digital platforms used above 3 stars, it has more than 5 recommendations in the different hotel digital platforms used, it has a Likes percentage in the social networks’ posts more than 10% of the total of their followings in more than 90% of their posts, it has at least 5 hotel labels in the social networks’ posts per month, high volume of visits to the profile of the social networks, directories and hotel digital platforms. (The data can be obtained in each digital application—it is public information) and it has at least 5 mentions in the comments in the social networks, directories and hotel digital platforms. To carry out this evaluation, the social networks of each hotel were analyzed and the digital platforms in which it actively participates and it was given a score of 1 if it complied with any item.

The variable: “brand image evaluated by the competitors” was measured by asking the direct competitor hotel managers about the image of the evaluated hotel with a 7 point Likert scale. The measurement was carried out in a minimum of 1 hotel and a maximum of 5 hotels outside the evaluated hotel. The hotels invited for the measurement were from the same municipality where the hotel to be measured was located. On the other hand, the measurement was also carried out with the remaining 39 hotels with which this study was conducted.

The “growth” variable was obtained by directly asking the hotel manager about the growth in the occupancy in a percentage compared with previous year 2019 to the beginning of 2020 January, February, March, taking into account that Colombia entered into a quarantine due to Covid 19, concluding in the month of April.

The “use of capacity” was evaluated by directly asking the hotel manager about the use of the capacity during 2019. This was expressed in a percentage, based on the statistics of each hotel.

The “Profit” variable was obtained with the ROA—return on assets results, which were provided by the interviewed hotel managers.

The variable: “return on investment in digital marketing” (social networks, hotel digital platforms, directories, among others)” was obtained for the year 2019 by subtracting the investment in digital marketing from the income and the result of the subtraction, dividing it by the investment in digital marketing.

Finally, the variables of basic control were added: age of the company, size evaluated in the number of rooms and by the hotel category in stars.

4. Analysis and Results

In order to evaluate the data obtained from the analyzed cases, a Qualitative Comparative Analysis (QCA) was used. This technique permits evaluating the effect of different configurations of the variables (conditions) in a specific outcome. In this study, the main conditions are the use of the different digital marketing tools and the performance as the outcome, measured in different ways. In the same way the outcome is evaluated too by means of the different degrees and forms of participation in the cluster in the hotel performance.

The relationships between the variables of this study are complex and although they can be correlated in an independent way, this relation is not always significant. If the theoretical framework represents the strong effects of the conditions on the result which are not shown in the data, this can be due to a complex causality and asymmetrical relations. QCA permits detecting the configurations (combinations of variables) which are necessary or sufficient in order to cause a result [58].

Because most of the variables are not dichotomous (all the variables except “membership in the cluster”), fsQCA was used for the study. In order to evaluate the non-dichotomous variables with this software, first, it is to calibrate them, establishing the full membership, crossover and full non-membership thresholds for each variable. This was carried out in the assessment of each variable for the most/least skillful and effective hotels in the use of the specific digital marketing tools and the most/least active and conscious members of the cluster. The calibration was also performed for the performance variables.

The variables: Twitter and LinkedIn were not evaluated since their level is very low for all the analyzed hotels without exception (a score of 1 in the two variables).

The necessary digital marketing tools(conditions) for the presence and absence of each type of general performance (capacity use, growth and profit) are shown in

Table 2. Analysis of digital marketing tools necessary conditions for general performance.

Outcome
	Capacity Use		Growth		Profit
Conditions	Consistency	Coverage	Consistency	Coverage	Consistency	Coverage
Website	0.31	1.00	0.48	0.91	0.47	0.85
Digital platforms use	0.81	0.86	0.95	0.59	0.98	0.59
Blog	0.17	0.99	0.29	0.99	0.30	0.98
Facebook	0.72	0.98	0.92	0.74	0.85	0.65
Instagram	0.42	0.99	0.66	0.92	0.60	0.80
Google AdWords	0.38	0.99	0.57	0.87	0.57	0.84
YouTube AdWords	0.13	0.99	0.20	0.94	0.21	0.95

.

Table 2 shows that only the use of digital platforms is a necessary condition for growth and profit (consistency higher than 0.9), although for the capacity use, the digital platforms consistency is only 0.81. Facebook is also necessary for growth, although its consistency is relatively low for capacity use and profit.

The required digital marketing tools for the presence and absence of each type of marketing performance (digital marketing return, internet brand image and brand image) are shown in

Table 3. Analysis of digital marketing tools necessary conditions for marketing performance.

			Outcome
	Digital Marketing Return		Internet Brand Image		Brand Image
Conditions	Consistency	Coverage	Consistency	Coverage	Consistency	Coverage
Website	0.23	0.70	0.32	0.99	0.45	0.86
Digital platforms use	0.72	0.72	0.88	0.86	0.98	0.62
Blog	0.11	0.60	0.99	0.18	0.28	0.99
Facebook	0.54	0.69	0.72	0.95	0.91	0.74
Instagram	0.29	0.66	0.44	0.99	0.68	0.96
Google AdWords	0.25	0.61	0.39	0.99	0.53	0.83
YouTube AdWords	0.11	0.81	0.13	0.96	0.21	0.98

.

The necessity of digital marketing tools in each type of marketing performance varies considerably. For the brand image (assessed by the competitors), digital platforms use and Facebook are the necessary conditions to obtain a good result (consistency over 0.9). For the Internet brand image, assessed by means of objective measurements, only the blogs fulfil the consistency parameter. Any condition is necessary for the digital marketing return.

The necessary cluster variables (conditions) for general performance and marketing performance are shown in

Table 4. Analysis of cluster necessary conditions for marketing performance.

Outcome
	Capacity Use		Growth		Profit
Conditions	Consistency	Coverage	Consistency	Coverage	Consistency	Coverage
Cluster membership	0.57	0.81	0.74	0.62	0.78	0.63
Cluster cooperation	0.27	0.76	0.31	0.51	0.32	0.52
Cluster act. participation	0.34	0.97	0.51	0.86	0.55	0.89
Time in cluster	0.50	0.91	0.67	0.72	0.76	0.78
Cluster network position	0.51	0.89	0.70	0.71	0.74	0.72

and

Table 5. Analysis of cluster necessary conditions for digital marketing performance.

Outcome
	Digital Marketing Return		Internet Brand Image		Brand Image
Conditions	Consistency	Coverage	Consistency	Coverage	Consistency	Coverage
Cluster membership	0.51	0.68	0.68	0.92	0.71	0.60
Cluster cooperation	0.25	0.68	0.33	0.89	0.24	0.40
Cluster act. participation	0.26	0.69	0.35	0.97	0.47	0.80
Time in cluster	0.43	0.74	0.56	0.97	0.68	0.74
Cluster network position	0.46	0.75	0.58	0.96	0.70	0.72

, respectively. Any cluster variable is necessary for any type of performance (consistencies are below 0.9 in all variables and outcomes).

The truth tables with all possible combinations of effectiveness in digital marketing tools (configurations) for each performance (outcome) are shown in

Table 6. Fuzzy set Qualitative Comparative Analysis (fsQCA): Digital marketing tools configurations leading to positive general outcomes.

Sol.	Path	Raw Coverage	Unique Coverage	Consistency
1	~F *~I *~B *~W *~GA→Capacity use	0.34	0.08	0.52
2	DPU →Capacity use	0.36	0.07	0.75
3	F *I *DPU *W→Capacity use	0.20	0.11	1.00
4	F*I*DPU*B*GA→ Capacity use	0.14	0.09	1.00
Solution coverage = 0.69; Solution consistency = 0.68; Outcome: Capacity use
1	~F *~I *~B *~W *~GA→Growth	0.20	0.02	0.18
2	DPU→Growth	0.32	0.09	0.40
3	F *I *DPU *W→Growth	0.33	0.18	1.00
4	F *I *DPU *B*GA→ Growth	0.25	0.15	1.00
Solution coverage = 0.76; Solution consistency = 0.44; Outcome: Growth
1	~F *~I *~B *~W *~GA→Profit	0.31	0.00	0.27
2	DPU→Profit	0.42	0.06	0.50
3	F *I *DPU *W→Profit	0.30	0.14	0.86
4	F *I *DPU *B *GA→Profit	0.27	0.16	1.00
Solution coverage = 0.81; Solution consistency = 0.45; Outcome: Profit

* W = Website; DPU = Digital platforms use; B = Blog; F = Facebook; I = Instagram; GA = Google Adwords; ~ = Non.

(general outcomes) and

Table 7. fsQCA: Digital marketing tools configurations leading to positive marketing outcomes.

Sol.	Path	Raw Coverage	Unique Coverage	Consistency
1	~F *~I *~B *~W*~GA→Internet brand image	0.38	0.08	0.55
2	DPU→Internet brand image	0.41	0.09	0.83
3	F *I *DPU *W→Internet brand image	0.20	0.11	1.00
4	F *I *DPU *B *GA→Internet brand image	0.15	0.09	1.00
Solution coverage = 0.75; Solution consistency = 0.71. Outcome: Internet brand image
1	~F *~I *~B*~W *~GA→Digital marketing return	0.51	0.18	0.73
2	DPU→Digital marketing return	0.44	0.09	0.86
3	F *I *DPU *W→Digital marketing return	0.13	0.05	0.62
4	F *I *DPU *B *GA→Digital marketing return	0.09	0.03	0.58
Solution coverage = 0.75; Solution consistency = 0.69; Outcome: Digital marketing return
1	~F *~I *~B *~W *~GA→Brand image	0.27	0.019	0.25
2	DPU→Brand image	0.42	0.18	0.53
3	F *I *DPU *W→Brand image	0.32	0.18	0.98
4	F *I *DPU *B *GA→Brand image	0.24	0.15	1.00
Solution coverage: 0.84; Solution consistency: 0.50; Outcome: Brand image

* W = Website; DPU = Digital platforms use; B = Blog; F = Facebook; I = Instagram; GA = Google Adwords; ~ = Non.

(marketing outcomes). The reduction of rows was performed using the Quine-McCluskey algorithm that yields the minimally sufficient configurations to produce the outcome. The coverage indicates the empirical relevance of each solution (number of cases that satisfied the combination). The consistency quantifies the degree in which cases sharing the same configuration share the same outcome.

The truth tables with all possible combinations of effectiveness in digital marketing tools (configurations) for each performance (outcome) are shown in Table 6 (general outcomes) and Table 7 (marketing outcomes).

The general outcome most sensitive to digital marketing tools is capacity use and growth. In both cases, they respond very positively (paths 3 and 4) to a good combination of Facebook, Instagram and digital platforms, supported by a web site or a blog and google AdWords. The profit behavior is also similar but path 3 only has a consistency of 0.86.

Table 7 shows that the digital marketing return is erratic and complex and the ratio of the benefits obtained from the digital tools compared with their costs cannot be evaluated only with the variables considered. For the Internet brand image, the combination of Facebook, Instagram and digital platforms is a good policy (consistency of 1.00), which can be combined with an excellent web site (path 3) or with a blog and google AdWords (path 4). The same results are obtained for the brand image assessed by the competitors.

The truth tables with all possible combinations of the cluster variables for each performance (outcome) are shown in

Table 8. fsQCA: Cluster variables configurations leading to positive general outcomes.

Sol.	Path	Raw Coverage	Unique Coverage	Consistency
1	CM * TC * CNP→Capacity use	0.46	0.43	0.91
2	CM * CC→Capacity use	0.05	0.02	0.57
3	~CM→Capacity use	0.42	0.42	0.62
Solution coverage = 0.91; Solution consistency = 0.72. Outcome: Capacity use
1	CM * TC * CNP→Growth	0.62	0.59	0.72
2	CM * CC→Growth	0.03	0.00	0.19
3	~CM→Growth	0.26	0.26	0.21
Solution coverage = 0.88; Solution consistency = 0.41; Outcome: Growth
1	CM * TC * CNP→Profit	0.70	0.64	0.78
2	CM * CC→Profit	0.07	0.01	0.42
3	~CM→Profit	0.22	0.22	0.18
Solution coverage = 0.93; Solution consistency = 0.42; Outcome: Profit

* CM = Cluster membership; CC = Cluster cooperation; TC = Time in cluster; CNP = Cluster network position; ~ = Non.

(general outcomes) and

Table 9. fsQCA: Cluster variables configurations leading to positive marketing outcomes.

Sol.	Path	Raw Coverage	Unique Coverage	Consistency
1	CM * TC * CNP→Internet brand image	0.51	0.48	0.97
2	CM * CC→Internet brand image	0.09	0.06	1.00
3	~CM→Internet brand image	0.32	0.32	0.45
Solution coverage = 0.90; Solution consistency = 0.68. Outcome: Internet brand image
1	CM * TC * CNP→Digital marketing return	0.41	0.37	0.75
2	CM * CC→Digital marketing return	0.05	0.02	0.56
3	~CM→Digital marketing return	0.49	0.49	0.67
Solution coverage = 0.92; Solution consistency = 0.69; Outcome: Digital marketing return
1	CM * TC * CNP→Brand image	0.63	0.59	0.74
2	CM * CC→Brand image	0.06	0.02	0.40
3	~CM→Brand image	0.29	0.29	0.25
Solution coverage: 0.94; Solution consistency: 0.45; Outcome: Brand image

CM = Cluster membership; CC = Cluster cooperation; TC = Time in cluster; CNP = Cluster network position; ~ = Non. Note: *, logical AND logical negation.

(marketing outcomes) respectively.

Table 8 shows that the active cluster membership does not assure a good general performance except for capacity use (consistency = 0.91) that is reached only with a good cluster network position and with time in the cluster (path).

For marketing outcomes, the cluster variables show better results than for the general outcomes (Table 9) but only in the Internet brand image. For this outcome, there are two paths of success: a good position in the cluster network combined with time in the cluster (path 1) and an intensive cooperation with other members of the cluster (path 2). It is interesting that the participation in the formative activities of the cluster does not appear in any path that results in any positive marketing outcome.

These findings support both hypotheses. It must be said that for Hypothesis 2, the special relevance of cluster membership for small and medium hotels can only be analyzed by studying, on a case by case basis, the positive results in path 3 in Table 8 and Table 9. The poor results that lower the consistency in this path (no cluster membership) are mostly due to the small and medium hotels, whereas the big hotels that do not belong to the cluster obtain good results in marketing performance and the general performance too (data not shown).

Together with the most relevant digital marketing tools and their best combination, the results show in which hotel performance dimensions they are more effective. Another important results extracted from the analysis is that clusters can enhance considerably the use of marketing tools, especially for those hotels with small size. The most surprising result is that cluster cooperation and to occupy a good cluster network position is the most secure way inside the cluster to obtain the digital competences that lead to a superior Internet brand image. Other clusters activities such as participation in formation events, conferences and seminars show ambiguity in results.

5. Conclusions

During recent decades, digital marketing has created new ways of obtaining relevant information about tourism companies and hotels, helping the users to find what they are actually looking for, preventing negative experiences in their tourism and leisure trips [59]. Hence, it is of vital importance for the tourism companies in general and hotels in particular and hotels to make the proper use of the digital marketing tools, in a strategic way, Hotels must understand how each digital tool affects to their performance dimensions and how continually improve by means of the information that the digital platforms offer.

The research performed in this article shows that the hotels with the most development, the best financial strength and years of experience in the La Guajira Department, Colombia, have created the proper transition to digital marketing, adapting to the requirements of today’s market. On the other hand, it also showed that a tourism cluster is an effective platform to qualify the small hotel companies towards growth through the proper use of the digital marketing tools. These tools have proven to be better used by hotels with great collaboration in the cluster and placed in a good network position than the other small hotel companies which are not a member of a cluster or limited their cluster participation to simply attending formation activities. The digital marketing effects are mostly reflected in generating customers and creating a brand image

The research found that the most effective digital marketing tools used by the tourism cluster of the Colombian La Guajira Department are: Facebook, Instagram and market places such as: Booking.com, Trivago.com, Tripadvisor.com and Atrápalo.com. On the one hand, it was found that the websites of the entire La Guajira region are not very competitive. They lack good online customer service via web chats, multilingual translators, online payment links, online reservations; they also lack online booking channels and the option for customer feedback.

On the other hand, it showed that the strongest hotel companies which are members in the tourism cluster, have web sites with a good positioning in the search engines and are equipped with excellent customer service. This Internet positioning rely more in the cluster collaboration and network position of the hotels than in the formation activities organized by the cluster management for all its members This improvement in digital competences is linked to the adoption of collaborators’ better practices and the awareness that the customers are captured through the Internet.

One of the most important contributions of this work to the current state of art is the analysis of the value of cluster membership for small hotels in the implementation of digital marketing tools. Yet, few empirical works study the specific cluster activities that most favor the integration of digital tools in marketing initiatives. At the same time, the principal digital marketing tools are assessed, not only individually but in combination.

The Colombian La Guajira region currently has huge growth opportunities in tourism options due to the exotic wealth that it possesses and its beautiful landscapes full of art and culture but in turn, there are many shortcomings in the digital business development. Consequently, based on the data obtained in this article, the creation of networks between the companies of this region will help each company to grow and develop the region’s economy.

Regarding the limitations of the study, the most patent disadvantage is that the set of data was obtained from a single cluster. Besides, this work is based on a small number of cases. Although fsQCA is useful for exploratory research and the combinations of digital marketing tools and cluster variables for successful performances were detected automatically by the software, the number of cases (40) was low for the high number of possible combinations of conditions (7 conditions in the case of digital marketing tools). Not all the combinations were present in the cases studied, so certain paths of success could have been neglected.

In order to overcome these limitations, future research should confirm the results obtained in this study for other hotels in regional clusters in areas underdeveloped. Besides, other organizational variables regarding the internal functioning of the cluster should be included.