ICT as a Support for Value Chain Management in Tourism Destinations: The Case of the City of Cuenca, Ecuador

Abstract

The accelerated development of information and communication technologies (ICTs) has had an impact on the way tourism is carried out today. The concept of smart cities and smart destinations is gaining momentum, which also requires smart consumers, i.e., informed, communicated, and connected. In this sense, the application of the value chain concept to tourism implies reconsidering the weight of digital technologies in its structure and, therefore, in the decision-making process of current and potential tourists. The study aims to demonstrate the need and convenience of incorporating technology as an innovative factor in the management process of the tourism value chain and its contribution to the positioning of the destination, taking the city of Cuenca (Ecuador) as a case study. The contributions are, firstly, the ICT adoption as an innovation factor in the value chain. In addition, through a survey of foreign tourists, it was verified that ICTs are a trend as a personalized communication channel, which contributes to valuing the integral tourism offer of the territory.

1. Introduction

Sustainable tourism has an effect on territorial development because it contributes to the financing of productive processes and services, organized in chains that increase the value of the local tourism product. Furthermore, they increase business competitiveness and form economies of scale based on external processes, reduce transaction costs, increase local value added, generate employment, promote productive innovation, and make efficient use of endogenous resources [1,2].

Based on the above, it is understood that the true final tourism product is of a “local” scale and its management implies the commitment of a government administration at that level. The tourist travels to a destination to consume its environment, its tourist resources, its services and infrastructure, its tourist establishments, its culture, and its people. The aggregate sum of these factors makes up the tourism product [3].

The importance of tourism as a development alternative is closely linked to the growth dynamics of this activity in recent times. Globally, this grew at a rate of 3.8% in 2019; arrivals reached a total of 1 461 million [4], however, by the first half of 2020 they were reduced by 65%, an unprecedented plunge caused by the closure of borders worldwide and the introduction of travel restrictions in response to the COVID-19 pandemic [5]. This situation continued over the course of 2021 and, between January and May of that year, tourist arrivals fell by 85% compared to the same period in the pre-pandemic year of 2019, or 65% during 2020 [4]. Little by little, borders are reopening, but in the short term economic losses for the sector will continue to increase. However, this situation will gradually reverse at the end of the pandemic, and tourism will again be consolidated as an important factor that generates alternatives for the improvement of people’s quality of life.

In this sense, it is necessary to pay attention to the structure of the tourism value chain and the weight of technologies in this structure. It is because the advance of information and communication technologies (ICTs) and the rise of the digital era with the massive exploitation of the Internet represent a contribution of value that makes it necessary to recognize their significance and validity. Throughout history, the successive introduction of new technologies has acted as a generator of change. These changes not only favor the advancement of science, but their repercussions extend to culture and, of course, to all areas of society, including the media [6].

With respect to Ecuador, historically, the country has followed a development pattern based on primary production, which, conditioned by the unequal exchange at the international level, has led to a dependence on products originating mainly in the agricultural sector [7].

Given this situation, the country’s policy is aimed at supporting the development of tourism and technology, as well as its bidirectional relationship to achieve value contributions through its incorporation into a digitized management system. This process positively affects the competitiveness of the tourism offer in terms of differentiation and cost. At the same time, it provides an integrated experience of respectful, natural, and social interaction for the tourist.

In the country in 2019, entries reached 2,043,993 visitors, decreasing by 16% (starting to decrease from August) compared to 2018, a year in which there was an increase of 51% compared to 2017, foreseeing at this time a sustained growth in the number of visitors [8]. (The statistical data taken into account are those corresponding to the year 2019, before the pandemic, given that, after the pandemic, the drop in visitors caused by it was 77% [5], which does not constitute a regularity.) Consequently, this dynamic of entries to the country favored up to that moment the presence of tourists in the city of Cuenca.

According to data provided by the Strategic Tourism Development Plan for the Cuenca Destination and its area of influence [9], Cuenca is internationally considered one of the most important cities in Ecuador and South America. It has been a recipient of international awards and converted into one of the top ten cities with potential, not only for temporary visits, but also for permanent residence, and is preferred by senior citizens.

Based on this background, the following was identified as the objective of the study: to demonstrate the need for and convenience of incorporating technology as an innovative factor in the management process of the tourism value chain, as a contribution to the positioning of the destination. The methods used at the theoretical level were: historical–logical, analysis–synthesis, and hypothetical–deductive; the empirical methods were based on the use of documentary analysis techniques for the collection of secondary information and questionnaires for the collection of primary information.

Therefore, the research answered the following questions:

• Given the advances in technology and its influence on tourism, is it possible to propose a new structuring of its components?
• Can the profile of the current tourist, who comes to the city of Cuenca, be considered a starting point for the design of new products?

In addition, considering that technology has a great influence on the distribution and communication channels, in response to this it is possible to consider the following hypotheses:

H1. 

Trends in tourism distribution point to the coexistence of traditional channels and the use of ICT.

H2. 

Trends in tourism distribution point to the prevalence of ICT use.

An analysis was made of the tourist profile by segmentation variables (age, origin, economy, preferences) and, additionally, the relationship between the profile of the tourists surveyed and their evaluation of the city’s tourism resources was evaluated. These elements of analysis complemented the hypotheses proposed and served as a basis for defining lines of action with respect to the management of tourism in the city using technology as a source of benefit.

2. State of the Art

This section analyzes the main theoretical approaches on the influence of technology on tourism management. The increase in its significance in this process demonstrates the need for a value chain proposal as a transversal axis that tends to create a tourist destination as an integrated offer. Its content answers research question No. 1.

2.1. Value from Today’s Perspective

In the field of business and especially under a marketing approach, the value of the category is assumed from the customer’s perception. First, according to the level of satisfaction of their needs, in correspondence with the attributes offered by the product. Then, according to the perceived preference and evaluation of these and the results of their consequences derived by use and ease of achievement of objectives and purposes [10] but also by the value in monetary terms of the technical, economic, service, and social benefits in exchange for the price paid for the market offer [11]. This complements the interactive, relative, and preferential experience [12], the positive function of what is received, the negative function of what is sacrificed [13], net value which is the relationship between what the consumer gives and receives, and perceived value which is the difference between what the consumer incurs and receives [14]. It is understood that competitiveness is the amount that buyers are willing to pay for what the firm offers [15]. Value, therefore, is made to correspond to utility/profit and exchange.

Value identification is the fundamental concept from which the value chain is defined [16,17], as a form of articulation in which its actors plan, prepare, organize, coordinate, and collaborate so that the product reaches the market with the characteristics required by end consumers. To this end, the direct and indirect actors in a chain must establish an alliance so that, in all processes, the product maintains or incorporates value.

According to Porter [14], the value chain is the set of activities that are carried out to design, produce, bring to market, deliver, and support its products, in which primary and support activities are distinguished and from which the sources of competitive advantage are derived.

It is based on the concept of the production chain, whose existence and interrelation of its components are necessary but not sufficient conditions for satisfying demand. Hence the need to distinguish between the production chain and the value chain, since, if the availability of a product on the market depends on a production chain, the sustainability of this chain depends to a large extent on the market’s stable acquisition of that product and, in turn, depends on the value that the product contains. Therefore, a productive chain must be organized and developed to generate value and not simply products.

In the praxis of tourism development, territorial and sectorial approaches are often combined and the promotion of value chains thus becomes a component of broader economic and social development programs and not just at the local or destination level.

2.2. Value Chain in Tourism

One of the objectives of structuring the tourism value chain is to achieve a more equitable redistribution of income and benefits, improving market access conditions, and offering greater bargaining power to tourism stakeholders with fewer resources. Therefore, any chain initiative must start from the market and analyze in detail the commercial possibilities that exist for small tourism producers and microentrepreneurs.

Authors who have addressed the issue of the value chain in tourism base their analysis on Porter’s approach, contextualizing it to the singularities of this economic activity. Among these criteria are those that emphasize the value system as an integration of primary and support activities from different perspectives. The primary activities are those that occur in the production process of the tourism product and the support activities that enable the development of the former [18]. The basic activities are those commercial activities that provide the tourism product and support its infrastructure [19].

Other authors emphasize the integration of actors and related activities [20,21,22,23] and the value system and chain performance, comparing the measurement of performance in the manufacturing and tourism industries. They emphasize the supply and distribution chain of the tourism package [20], with emphasis on the use of ICTs as a contribution to the exchange of information that favors efficiency in the link between the different links and the decision making of the actors involved in each process [21]. They also carry out level analysis, planning, operation, and marketing [24] and formation of clusters that collaborate strategically to achieve long-term objectives [25].

So, there is a great versatility in the criteria regarding the concept and components of the tourism value chain. All, however, agree that it is determined by a process in which different actors interact and on whose synergy the creation of value depends and, therefore, tourist satisfaction. However, the explicit statement of the role played by the different actors is found in Yilmaz and Bititci [20] and especially in Zhao et al. [22], regarding the importance of integrating basic services into the planning of tourism offer. The point of view of the UNWTO is relevant, in which it defines the value system as the interdependent set of companies that, when articulated, cause synergies and a higher quality of the economic activity linked to tourism [26].

Other authors [27] are more explicit in their analysis, stating that to position the destination in the market, it is necessary to adapt the territory for tourism activity, define the target public to which the product will be directed, structure a coherent offer, and conceptualize the value to be offered to the market. Then, they describe how this product will be distributed, bringing it closer to the tourist and, finally, ensuring coherence between the product planned and the product finally offered. Benavides gives greater significance to the role played in the competitiveness of the value chain by the management of information and knowledge through the formation of networks [25].

The truth is that the management model based on locally available resources aims only at obtaining comparative advantages for the destination. This model has ceased to be relevant to give way to other models based essentially on strategies that seek competitive advantages throughout the tourism value chain; in this sense, the authors agree with the assessment that the tourism value chain activity model could be more appropriate using both tourist and tourism supplier side analysis, emphasizing both quantitative and qualitative evaluation of the tourist experience, before, during, and after the trip [28], but we go further and consider that the integration of ICTs in the strategic and operational processes of tourism points to a new management model [29].

2.3. Definition of the Tourism Destination Value Chain, Based on the Concept of an Integrated Offer

In correspondence with the objective set out in the investigation, the authors understand that this analysis is valid; however, it is considered first that the tourism value chain is based on the conditionality of the resources/attractions existing in the area, their hierarchy and territorial planning and management, and the integrated supply approach. The tourism inventory is an important element to support decisions on territorial planning [30]. It is necessary to territorialize decisions by creating management units and making use of digital tools that allow them to be consistent with land use planning in order to preserve heritage [31].

This is the main element for managing tourism from the perspective of the destination; on this basis, the benefit which in terms of satisfying leisure needs increases the value of the offer and articulates the peripheral and complementary services is determined.

Secondly, the need for and convenience of adopting technology in the preparation of this offer is affirmed, not only as a facilitator of information about the destination, but also as an essential means of innovation in each of the components of the chain, being transversal to its entire structure.

Based on the above, it is understood that the analyses carried out in relation to the role played by technology in adding value to the tourism chain emphasize the use of information technologies. This criterion is accepted insofar as the use of these techniques provides information from which it is possible to generate future changes in any of the phases of tourism offer management, and this is where their main contribution lies. However, it is not simply a question of using tools that allow the capture of more information from the tourist or new channels of communication and access to the offer, but of converting this information into knowledge for improvement in any of the phases of the management and decision-making process of tourism consumption.

From this perspective, it is up to local public administrations, through the exercise of governance, to assume a protagonist role in the generation of alliances between public, private, or mixed service providers and the host community, in order to generate an integrated offer of the destination. This must consider the particularities of each product and, by generating synergies, develop a value creation process, an essential element to achieve the competitive advantage that ensures the differentiation and positioning of the destination, articulated with the demand that translates into the experience lived by the tourist.

The management of technology and knowledge supports this creation of value, as it allows linking all the links and fostering the creativity of the participants in the tourism experience. Significant improvements of innovative origin must be present throughout this process, linked to concrete activities before, during, and after the tourist’s visit. With this it is possible to approach the basic pillars of the so-called “smart destination”, translated into: governance, innovation, technology, universal accessibility, and sustainability [32].

The authors propose a new structure and composition of the chain that is represented as the scheme shown in Figure 1. The explanation of each of the defined phases is detailed below.

2.3.1. Phase I: Product Design as an Integrated Offer (Value Creation)

There are economic activities whose dependence on resources is the starting point. Tourism is one of them and, as explained above, the existing resources/attractions in the area, organized and hierarchized in an inventory, and planning based on territorial organization will be the basis on which a destination can be structured and the essential source of motivation for tourist flows.

In this sense, and according to the marketing approach [15], the structure of the tourism product comprises first a core product or basic service that depends on resources and attractions. Subsequently, there is an associated peripheral product/service, necessary for the development of the previous one and without which it would be provided in very limited conditions or not be provided. Finally, there are complementary products/complementary peripheral services that enhance the overall service, adding value, attractiveness, and entertainment whose diversity depends on the degree of creativity used in their design are materialized in the versatility of the activities proposed to the tourist client.

The objectivity of these approaches assumes that the marketing approach in tourism presupposes the clear identification of market segments and their profiles, so that organizing activities consistent with their expectations is one of the keys to success. Demand makes it possible to obtain arguments for the design of the offer, make adjustments to it, and be creative in the search for tourist satisfaction based on the practice of different modalities.

Gómez systematizes the aspects that must be taken into account for the design of the offer in a tourist destination. From this perspective, the chain is formed from a series of interdependencies of actors and processes, and in tourism, as a particularity, the activities do not follow one after another, but intertwine horizontally, most of the time generating a complex network. In this dynamic, the government assumes a preponderant role in the destination as it is responsible for establishing strategies that define alliances between the actors of accommodation, catering, recreation, travel agencies, infrastructure, information, access, transport, basic services, food supply, and others necessary for the tourist’s stay. This ensures that the implementation of new ideas is aligned with the territorial planning proposed in the locality and contributes to sustainability in the management of the destination, regardless of the administrative demarcations that this entails [33].

2.3.2. Phase II: Distribution and Communication (Value Contributions)

Distribution and communication play an important role in the development process of a tourist destination. The destination is sold before the tourist visits the place, therefore, what he sees through images and hears and the sales effort made from the different channels, including web pages or other technological media, decide his visit.

The most important thing in this phase is to define the distribution channels and how organically the tourism service providers in the country are linked, so as to connect lodgings and tour operators with travel agencies and tour operators and/or independent tourists, who have organized their own travel route directly through the Internet.

It is interesting that the destination is communicated, distributed, and positioned on the basis of an umbrella brand, which defines the attitude of the destination towards the different modalities, its attributes, and the contributions of value given by the creative spirit of the managers. The belief on the part of the tourist, his hope of living an unforgettable experience, depends a lot on the people or organizations and institutions that execute these processes.

2.3.3. Phase III: Value Proposition

The efficiency with which the two previous phases are managed will determine the results in terms of the integrated experience lived by the tourist. The evaluation of the fulfillment of their expectations will show the degree to which the destination’s objectives and positioning attributes aligned with the competitive advantage have been met.

The expectations that have been met, their opinions of improvement, and the changes that may occur in demand caused by the micro- and macroeconomic factors that influence it, such as price (throughout the chain), substitutes, the economy of the issuing/receiving country, among others, are the starting point for modifying and increasing the value added to the tourism offer.

2.4. Knowledge Management and the Use of Technology, Drivers for Value Creation

This section constitutes the main reflection, which, from the analysis of the influence of technologies in tourism, supports the proposal of the structure of the value chain.

In the analysis of 188 documents published in English, Vidal, Rodríguez, Rubio, and Narbona come to the conclusion that: the knowledge about the use of technology is increasing, and more and more studies are analyzing how to use ICT to provide a competitive advantage and in turn help to halt the damage caused by tourism activity [34].

Since tourism is a service, its quality depends on human talent in the use of available resources. Its attachment to knowledge management and technology is intrinsic; thus, the use of tacit knowledge by the members of the community, their legends and experiences, their sharing, the interaction among them, the stimulation of creativity, and the transformation of this tacit knowledge into explicit knowledge, which can be used in the product’s distribution processes, are important sources of value creation.

The participation of the community in the diagnoses of the community and their perspective for the search for solutions linked to tourism products increasingly demonstrate their effectiveness [35]. The use of these elements by tourism managers is essential, and in this context technology becomes a tool that connects them and facilitates the contribution of value from the processing of information for the design of new strategies.

The theoretical approach that supports the importance of technology in the management of the value chain is argued from two perspectives: on the one hand, the weight that small businesses have in tourism and, on the other, the current demands in favor of an integrated tourism experience. This requires managing the activity in the form of multi-channel networks that make up a destination, that is to say, a territory/people logic above an administrative logic.

Of course, the alliances that contribute to the synergies that achieve from the formation of both vertical and horizontal networks go through the filter of the competitive advantages that each company achieves, in relation to resources, markets, and technologies. With this as the source, to provide valuable products to consumers, these elements have a significant importance in the performance of the alliance [36].

With respect to this issue, in the area of SMEs, the benefit achieved by using ICTs that support knowledge management (e.g., groupware, videoconferencing, Internet, Intranet, etc.) stands out, basically aimed at facilitating interconnection and integration between people through the rapid and effective exchange of information and knowledge, shortening in time and space distances that can go beyond administrative demarcations [37]. Given that these companies represent the largest proportion of the global business sector and contribute enormous benefits to the economy, boosting their development would be equivalent to developing the economy of the country where they are based [38].

However, studies linked to the effect of the transfer and use of technologies—beyond the use of ICTs—for these companies are poor, due to the difficulty of finding indicators that measure this effect. Pérez and Cruz show that companies in the commerce and construction sectors have the advantage, given their proximity to research centers, despite the fact that the need to include these aspects in this type of company to ensure their competitiveness in the market, regardless of the sector, is not questionable [39]. Therefore, in order for companies in the tourism sector to find competitive advantages, it is essential to adopt new technologies based on knowledge management. In this sense, information on tourists’ perceptions, attitudes, and behaviors contributes to decisions that mitigate the knowledge gap [40].

Tourism entrepreneurs have a high dynamic capacity influenced by factors such as knowledge, values, and experience, combining creativity and innovation to face crises [41]; small companies are flexible and their dynamic capabilities allow them to face crises in innovative ways by changing their business models [42].

The new scenarios imposed on tourism by the COVID-19 pandemic require tourism managers to take a proactive stance. This requires a change in methods and procedures, together with a more objective selection of market segments in line with the leisure needs of the localities. By betting on an alternative tourism that is different from mass tourism, it is a matter of assuming the approach of sustainability in all its dimensions, starting from the inclusion of innovation, taking advantage of the endogenous resources of the territory [43].

In particular, assuming the need to incorporate the necessary changes to the tourism value chain in accordance with what was stated above presupposes understanding that these technological tools can also be used in the design and development of new products, shortening the development cycle or increasing the number of alternative designs. The capacity of ICTs to process large volumes of information more quickly generates greater efficiency in all the processes involved in the chain. Despite the disadvantages regarding the use of technology in terms of reliability, security, maintenance costs, and transparency, suppliers and end users can increasingly use digital platforms more efficiently [44]. The use of e-commerce as a complete process for its implementation is still inadequately addressed and the studies focus on the pre-implementation phase, rather than implementation and post-implementation phases [45].

In addition to harnessing them, the use of these technologies can generate more activities linked to product design, based on market research, that visualize new opportunities through technological applications of netnography, neuromarketing, online research, and natural language processing (NLP) techniques, including sentiment analysis, text data mining, and clustering techniques, to obtain new scores based on consumer sentiment for different product features [46]. The tools that digital marketing offers include search engine marketing (SEM) and search engine optimization (SEO) [47], the combination of media, metrics that help to verify the fulfillment of objectives, structuring of conversion funnels, and inclusion of conversion rates that help to identify how effective actions have been to attract potential customers and build customer loyalty [48].

Furthermore, in the use of technology for interaction between multidisciplinary groups, qualifying the profile of the segment from quantitative data and its interrelation gives greater scientific accuracy to decision making with respect to the market. It integrates territorial tourism planning, the application of sustainability to the value chain, the incorporation of technology in the tourism experience and in the provision of services, the effective and efficient management of resources, and the capacity to respond to the needs and behavior of tourists [49]. Along the same line of thought, it can be said that technology offers benefits for maintaining an international presence in the global market at low cost, for forming alliances with other companies in the sector and even for reducing personnel for product management. Thus, innovation is facilitated; value chains are more flexible and consumers can design their own offerings. There is instant communication between the parties and, in addition, the technologies alert tourism companies about oversupply or overdemand of packages, which helps to define more competitive prices in such a way that their contributions go towards the search for competitive advantages in cost and differentiation.

This analysis takes on greater significance in the context of the transit of the destination towards the smart tourism destination (STD), in which reflection on the value chain based on knowledge management and technology becomes more relevant, as an emerging approach in terms of the high penetration of ICTs in tourism production and consumption; the need to ensure the environmental quality of destinations; to enrich the tourist experience; and to strengthen and communicate the attractions of the territory [50].

The term “destination” is an extensive, diverse, and complex concept to define, which can be specified from multiple angles and perspectives [51,52,53]. Nevertheless, in most of the definitions reviewed it is possible to find points of agreement that almost always emphasize the geospatial aspect of the phenomenon and those of functioning in economic terms: market, product, and psychological consumer motivation [51].

Thus, the destination represents the basic unit of analysis in tourism and recognizes three perspectives for its understanding: the geographical, easily recognizable area with geographical or administrative boundaries that tourists visit and stay in during their trip; the economic place where they stay the longest; and the psychographic area that constitutes the main reason for the trip. Served by the public, private, and mixed sectors, it can be a whole country, a region, an island, a village or a city, a center, or independent attraction [26].

Currently, the analysis acquires greater nuance when the expression STD is incorporated, since the use of technology has increased the nuance of the concept of smart cities and its evolution towards the STD [54]. The concept derives from smart cities as centers of knowledge, information management technologies, and information [55]; the deployment of ICT in the city can generate an innovative ecosystem supported by innovation and better management of city infrastructures and services [56].

As the Internet advanced, tourists adopted the role of content producer and began to upload photos, videos, and travel comments on Facebook, Instagram, Twitter, YouTube, even making recommendations of the sites or places they visited and the service they received [57]. The “open” movements—government, source, software, data, etc.—are now strongly emerging, which are the keys for today’s tourists. This has a great influence on the conception of the STD.

However, the ETS concept goes beyond the application of new technologies. It also serves to transform tourism destinations through the application of the governance model in the generation of innovative destinations and their full adaptation to the digital economy through quantitative and qualitative improvements in connectivity, sensorization, information systems, and online marketing [38]. These are interesting initiatives that make it possible to evolve towards innovative ecosystems that leverage the change towards improving the tourism experience and favoring the development of services and products based on ICTs.

The digital tourist, hyperconnected and multichannel, maintains a close link with mobile devices and the use of these technologies [56]; the practice of applying the concept depends on the type of destination and its territorial environment [58]. This approach moves towards “territorial intelligence” [39], which will integrate co-management with responsible governance, by taking into account the participation of the entire information-holding and interconnected community [59]. Territorial intelligence gives the destination a holistic approach, which goes beyond territorial criteria in favor of offering tourists an integrated experience [60].

3. Materials and Methods

The case study presented here is of the mixed, descriptive, and correlational scope research type, in accordance with the approaches developed [61]. It corresponds to a non-experimental cross-sectional design, which together with the use of qualitative techniques allowed us to collect primary information on the variables selected for the study, measure them, structure hypotheses, and thus find answers to the questions raised in the investigation, as a result of the application of the various methods and techniques described below.

The historical–logical method made it possible to characterize the phenomenon selected for the study, starting from its historical evolution, that contributes to understanding the process and is linked to the development of the object of study [62] through the search for bibliographical references that made it possible to update the state of the art.

The analysis–synthesis method [63] helped to define the conceptual framework around the use of ICTs in the tourism management process, the concept of the tourism destination, and its relationship with the value chain construct, based on the use of key words or descriptors.

In order to answer the first research question, the approaches made by various authors to the structure of the value chain were analyzed. The discussion provides a new conception of this, which points to two essential elements: the integrated value offer with a territorial approach and technology as a support for each component.

It is taken into account that the guiding thread that defines the value creation process is tourists, their perception of the benefit offered by the destination, and the prevalence of the channels they use to identify sources of satisfaction that are articulated with their needs and wishes.

Hence, the use the hypothetical–deductive method [63] made it possible, on the basis of the hypotheses proposed and from the use of statistical methods, to measure and analyze variables linked to the tourist profile, their perception of the existing resources/attractions in the locality, and the channels used to infer generalizations of the observed phenomenon, which are shown in the Results and Discussion.

The empirical analysis was carried out from the perspective of demand, since it is understood that the essential elements within the value chain of the tourist destination are given by the tourists, to whom the rest of the components are tributary. Their expectations connect and promote their interaction regarding the benefits caused by the main attractions of the tourist destination. For this purpose, a survey in the form of a structured questionnaire was used. It had two sections, the first of which contributed to gathering information with reference to the general data of tourists, country of residence, gender, age, level of education. The second section had 27 questions, 7 of them dichotomous closed questions, 20 semi-structured ones based on the Likert scale, and 1 open question to identify perceptions about the destination Cuenca.

The questionnaire was based on the following topics: characterization of the profile of the tourist visiting the destination, perception of the importance of the resources/attractions and activities to be carried out, assessment of the use of ICTs versus the use of traditional channels, quality of the offer, and opinion on the aspects of the destination that they liked the most. Consequently the questions were structured based on:

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Entry of foreign tourists to the city, by age, sex, country of origin, site visited before arriving in the city and intention to make Cuenca their residence.

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Availability of access to and use of ICTs to obtain information about the trip and organize their trip.

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Analysis of the perception of tourists regarding resources/attractions, their level of importance and main motivation for traveling to the city, thus expanding the segmentation variables, which can serve as a basis for product design and subsequent development of marketing plans with emphasis on the communication of the proposal.

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Perception of tourists in relation to the quality of the offer.

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Opinion on their general perception of the destination (open-ended question).

The analysis of the primary information allowed us to answer research question No. 2 and the hypotheses raised in relation to the channels used by tourists to access the town.

The pilot questionnaire was applied to a group of 60 tourists. Based on its results, the necessary corrections were made to the instrument and then the final version was applied to a random sample that reached a total of 419 tourists. The results were processed using the SPSS version 21 software.

To verify the random nature of the sample, the “streak test” was applied to the main demographic variables that allow differentiating between respondents, “gender” and “age”. For this, the following hypotheses were contrasted:

H0. 

The order of appearance of the values of the variable (Gender/Age) is random.

H1. 

The order of appearance of the values of the variable (Gender/Age) is not random.

The null hypothesis is accepted with a p-value = 0.498 (gender), p-value = 0.065 (age), and a confidence level of 1-α = 0.95 for both variables, so it can be assumed that the people in the sample had a random pattern.

Therefore, with what was previously exposed in a theoretical way, the procedure applied for the analysis of information and fulfillment of the objectives is summarized below.

• To favor the quality of the information, a data-curating process was undertaken. This was carried out through standardizing and codifying the information.
• For descriptive statistics, demographic and socioeconomic data were analyzed from the survey responses by applying univariate dispersion statistics and histograms. Meanwhile, to analyze demographic and economic data, perception of Internet payments, motivations, travel organization, activities, and image of the destination, multiple correspondence analysis was applied. In addition, to analyze the profile of the tourists, cluster analysis was used in the interest of identifying the groups of tourists.
• The sample randomness test was applied through the streak test to contrast the gender and age hypotheses.
• Exploratory factorial analysis was applied to characterize tourists according to their valuation of tourist resources. For this, a correlation matrix, analysis of total explained variance, autovectors associated with the selected factors, and reliability analysis by subset were used.
• The relationship between tourism activity and the use of ICT was analyzed through decision trees, which may determine the propensity for use as a distribution channel.

4. Results and Discussion

The results are presented in the order in which the research questions were asked:

• Section 4.1. Profile of respondents
• Section 4.2. Analysis of trends in preferences regarding resources/attractions
• (Section 4.1 and Section 4.2 are linked to research question No. 2)
• Section 4.3. Channel preference analysis for the travel decision

4.1. Profile of Respondents

Based on the theoretical approaches outlined in the previous section, and as described in the methodology, we proceeded to analyze the profile of tourists visiting the city, understanding that the characterization of the demand is the starting point that sets the sources of innovation of the destination’s offer. Therefore, it is convenient and necessary to determine the characterizations of tourists in order to show a value offer regarding the benefits/satisfiers that correspond to their preferences.

The city of Cuenca, founded as Santa Ana de los Cuatro Rios de Cuenca, also known as the Athens of Ecuador, is a city in the southern central part of the Republic of Ecuador and capital of the province of Azuay (Figure 2). It is located in a valley of the Andean system, at 2550 m above sea level, and surrounded by a mountainous system that houses an extensive lake system that bathes the city through its four rivers, from which it obtains its name. Cuenca is the third most populated city in the country, with 603,269 inhabitants, with a population growth of 15% in 7 years [64].

Once the sample was processed, it was observed at a descriptive level that the tourists interviewed registered the following patterns:

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38% come mainly from North America; followed by 34% coming from Western Europe;

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in terms of age, there were two main groups: young people between 20 and 30 years of age (34%), and adults over 45 years of age (34%);

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as for the level of training, 61% identify themselves as professionals;

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70% are visiting Cuenca for the first time;

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69% stated that they did not intend to move to Cuenca;

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64% stated that they were in Ecuador before coming to Cuenca, mainly in Quito (26%), Guayaquil (20%), and Baños (9%);

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78% said they had already planned to visit Cuenca when they arrived in Ecuador.

Regarding the economic aspect, 57% reported spending up to 20% or less of their annual income on their vacations per person. Sixty-nine percent stated that they would invest up to USD 1000.00 or less per person for their vacation in the city of Cuenca. Eighty-four percent consider Cuenca a “very cheap” to “reasonable” destination. Sixty-two percent consider that with the use of ICTs they save up to twenty percent compared to the family investment for the trip.

According to the description of the variables associated with the hypotheses, Scheme 1 shows the characterization of tourists in relation to age, gender, level of education, and country of origin. The result suggests that the respondents are distributed in two groups with greater significance: (1) American, Canadian, and Spanish adults, mainly male; (2) teenage pre-university students of German origin, mainly female; there is a third grouping of young people of other nationalities, mainly female university students.

Cuenca is a city that has commonly been described as a possible destination for residence, especially by people from the United States, so this variable was considered in the study to segment the tourists, since it could suggest activities related to information and advice regarding this need.

The profile of the tourists, analyzing the segmentation variable “people visiting the city”, can be classified into two groups. (1) North American adults (over 45 years of age) with the intention of residing, equivalent to approximately 29% of the total; and (2) young people (under 30 years of age) from the rest of the world, mainly from Western Europe, with no intention of residing, equivalent to approximately 63% of the total.

The cluster analysis shows that the first cluster covers 63% of the sample and is characterized—in general terms—by people coming mainly from Western Europe, who do not express their intention to settle in the city; they were in Ecuador before coming to Cuenca; they planned their visit as a short stay; their ages are between 26 and 30 years old; and they are visiting Cuenca for the first time.

The second cluster comprises 29% of the sample and is characterized—in general terms—by people from the United States, who express the intention of settling in the city; they were in the United States before coming to Cuenca; they planned the visit as a long stay; they are older than 45 years; and they are not visiting Cuenca for the first time.

The characteristics of each cluster suggest that while the first cluster comprises mainly young Europeans arriving in Cuenca with the intention of having a short stay, the second cluster comprises mainly North American adults arriving in Cuenca with the intention of settling in Cuenca.

In relation to the “economy” variable, as shown in Scheme 2 it is observed that the groups comprise: (1) North American adults, who consider the city a “cheap” to “very cheap” destination, who spent less than 10% of their income on the trip per person, and (2) youth and teenagers from the rest of the world, who consider the city a “reasonable” to “expensive” destination, who spent more than 10% of their income on the trip per person; as well as a marginal group of seven (7) respondents who consider the city a “very expensive” destination or who invested between USD 4001 and 6000 per person on this vacation.

In relation to their perception regarding the security provided by the use of the Internet to make payments, the data shown in Scheme 3 suggest that respondents are grouped as follows: North American adults who made their payments electronically, whose level of confidence is “high” with respect to these transactions, and consider that by this means they achieve savings of 40% or more; young people and adolescents from South America who did not make their payments electronically, whose level of confidence is “low” to “very low” with respect to these transactions, considering that by this means no savings are achieved; and young people from the rest of the world, who did not make their payments electronically, with a “medium” level of confidence with respect to these transactions and who consider that by this means savings of less than 40% are achieved.

From these data it can be inferred that the perception of those surveyed is in line with their income levels and the level of development of their countries of origin, with a clear difference in this aspect between tourists from North America and young South Americans.

A last segmentation variable used for the grouping of tourists was that of “preferences with respect to resources/attractions”. According to the following graph (Scheme 4), there is affinity (proximity) between tourists’ motivations for visiting the city, with “safety–hospitality” and “culture–history–nature” standing out. This grouping of tourists according to their motivations coincides with that carried out by Prada and Pesántez, who carried out work in this direction, highlighting that “a first one, which has been called “cultural” and which represents 31.82% of the sample, responds to a group of tourists highly motivated by the knowledge of the culture and traditions linked to the city of Cuenca” [65] (p. 90). The options “heritage” and “others” described patterns not related to the other categories.

From the analysis, two market segments are distinguished: tourists from the US with the intention of residing in the city who consider Cuenca as their final destination and young people from Europe and/or South America who are passing through, considering the town as a circuit destination. Thus, for this market segment, the city is classified as a circuit destination; the visit to the site in most cases is optional. However, given the natural environment that surrounds it, this could constitute a usable resource to extend the periods of stay, by generating complementary products and activities.

However, the groups coincide in relation to motivations for visiting the city. The cultural offer is currently poor and does not show differentiation in relation to the attention of these segments, the landscape richness that exists in its surroundings is poorly used, the absence of tourist products structured based on these elements dismisses this opportunity, and the level of creativity and innovation is low.

This information acquires particular relevance in terms of conducting marketing efforts for these market segments, using as a positioning concept in the first case the combination of culture and nature, specifically the scenic beauty of the surroundings of the city in which the Parque Cajas is located and the magnificent rural environments of the parishes that surround it. (Created by Interministerial Agreement A-203 of June 6, 1977. Located in the southern central part of the country, in the province of Azuay, canton of Cuenca. There are numerous tourist attractions, such as: Llaviucu Valley and Lagoon, Toreadora Lagoon, Illincocha Lagoon, Lagartococha Lagoon, Tres Cruces Hill, Taitachungo Lagoon, Burines Sector, Ventanas Sector, Caminatas, Virgen del Cajas, Paredones, Playas Encantadas Lagoon [66].) Secondly, the security offered by this destination is also relevant. In this way, it is possible to consider the design of the product based on the resources/attractions that the locality possesses, covering the first phase of structuring the value chain.

4.2. Analysis of Trends in Preferences Regarding Resources/Attractions

In order to deepen the level of preference of tourists with respect to the existing resources/attractions in the locality, information was collected based on the average rating of tourists with respect to resources/attractions having between 3 and 5 points, with the categories “Landscapes” and “Rivers and Lakes” registering the highest scores and “Religious Tourism” the lowest. It was evaluated if these ratings correspond to any pattern or profile of the interviewees that can be characterized. According to the exploratory evaluation carried out by means of factor analysis (FA) (fulfilling the applicability criteria according to the Kaiser–Meyer–Olkin test of sampling adequacy (0.753); Bartlett’s test of sphericity (chi-square 1156.620) and Cronbach’s alpha reliability (0.777)), the option “Dimension Reduction—Factor” of the SPSS software was used, obtaining the following results in a correlation matrix (

Table 1. Resource relationship matrix.

	LAN	RL	HSC	RT	MUS	HP	LC	MD	TH	TAA	ARQ
LAN	1	0.619	0.073	0.129	0.249	0.325	0.196	0.131	0.187	0.1	0.209
RL	0.619	1	0.026	0.07	0.147	0.283	0.177	0.067	0.197	0.134	0.205
HSC	0.073	0.026	1	0.321	0.249	0.218	0.147	0.254	0.263	0.096	0.049
RT	0.129	0.07	0.321	1	0.648	0.33	0.219	0.329	0.312	0.337	0.184
MUS	0.249	0.147	0.249	0.648	1	0.444	0.101	0.251	0.27	0.385	0.312
HP	0.325	0.283	0.218	0.33	0.444	1	0.382	0.413	0.398	0.188	0.34
LC	0.196	0.177	0.147	0.219	0.101	0.382	1	0.594	0.313	0.015	0.254
MD	0.131	0.067	0.254	0.329	0.251	0.413	0.594	1	0.343	0.169	0.3
TH	0.187	0.197	0.263	0.312	0.27	0.398	0.313	0.343	1	0.259	0.269
TAA	0.1	0.134	0.096	0.337	0.385	0.188	0.015	0.169	0.259	1	0.312
ARQ	0.209	0.205	0.049	0.184	0.312	0.34	0.254	0.3	0.269	0.312	1

Note: LAN = Landscapes, RL = Rivers and Lakes, HSC = Historical, Social, and Cultural Resources, RT = Religious Tourism, MUS = Museums, HP = Historical Places, LC = Local Communities, MD = Music and Dance, TH= Traditional Holidays, TAA = Traditional Agricultural Activities. Determinant = 0.04. Source: Statistical processing. Yellow color pairs of variables with the highest correlation (R > 0.59).

).

• The determinant of the matrix registered a value close to zero (Det = 0.04), likewise, the average correlation of the 2 × 2 combinations of variables was R = 0.25, which indicates that, although most of the variables maintain a significant relationship (not attributable to mere chance), there is a “weak to moderate” relationship.
• The pairs of variables that recorded the highest correlation (R > 0.59) were:

  -

  Museums/Historical Places, R = 0.65.

  -

  Landscapes/Rivers and Lakes, R = 0.62.

  -

  Music and Dance/Traditional Holidays, R = 0.59.

Next, the results obtained with the SPSS software for the total variance explained (Scheme 5 and the distribution of the variables by the components explained by the factor analysis from the components matrix suggest the presence of a pattern in the way of valuing the tourism resources consulted, grouped by the following valuation sets of tourism resources:

• Set A: “Landscapes/Rivers and Lakes”.
• Set B: “Museums/Historical Places/Architecture”.
• Set C: “Music and Dance/Traditional Holidays”.
• Set D: “Religious Tourism/Local Communities/Traditional Agricultural Activities/Local Traditional Gastronomy”.

The categories that showed less affinity with respect to the others were: “Religious Tourism” and “Local Traditional Gastronomy”.

According to the arrangement of the categories and their coefficients with respect to each component, it is interpreted that component 1 corresponds to a latent variable related mainly to tourism resources involving “Social Interaction”. Component 2 is related to “Cultural Activities” and component 3 is related to “Interaction with Nature”. This factorial structure offers important keys to organize tourism products in consideration of the demand according to the segments studied, based on product design and subsequent communication, taking advantage of the benefits of technology.

Prediction of the Valuation of the City’s Tourism Resources According to the Profile of the Respondents

This step consists of building and evaluating supervised classification models that predict the valuation of the tourist resource from the answers given by the tourists in the questionnaires. In other words, predicting the valuation of the categories contained in the question about the valuation of the city’s resources/attractions (dependent variables) from the other variables in the questionnaire related to the tourist’s profile and likes (independent variables).

Since most of the variables considered are categorical, the applicable methodology for modeling is based on decision tree algorithms.

The results of the selected models compared:

Set A—Categories Associated with Natural Resources: the results indicated in the confusion matrix of the “test set” recorded an overall accuracy of 85.4%. The accuracy for classifying the observations corresponding to tourists who assigned a high score to these categories (sensitivity) was 96.2% and the accuracy for classifying those who assigned a low score (specificity) was 9.1%. The following graph shows the grouping of tourists according to their preference for tourism activities associated with these resources.

As can be seen, in the Scheme 6 the tree discriminates the interviewees according to their valuation of the natural resources of the city. The node that groups the majority of interviewees who assigned a high score to this category (42.3%) corresponded to those who would like to do “Hiking” and are not “University Students” (indicated in red).

Set B—Categories Associated with Cultural Resources: the results indicated in the confusion matrix of the “test set” registered an overall accuracy of 67.5%. The accuracy for classifying the observations corresponding to tourists who assigned a high score to these categories (sensitivity) was 76.9% and the accuracy for classifying those who assigned a low score (specificity) was 57.9%. The following graph shows the grouping of tourists according to their preference for tourism activities associated with these resources.

The tree shows a node that groups the majority of respondents who assigned a high score to this category of cultural resources (21%) corresponding to travelers from: “Colombia”, “Hungary”, “Argentina”, “USA”, “Canada”, “Chile”, “Spain”, “Peru”, “Venezuela”, “Italy”, “Russia”, “New Zealand”, “South Africa”, “Ukraine”, “Uruguay”, “Czech Republic”, and “Sweden” and, in turn, regarding the activities they would like to do in Cuenca, they indicated “Historical Places” and did not indicate “Traditional Agricultural Activities”.

Set C—Categories Associated with Social Activities in the Scheme 7: the results indicated in the confusion matrix of the “test set” refer to an overall accuracy of 58.8%. The precision for classifying the observations corresponding to tourists who assigned a high score to these categories (sensitivity) was 78.6% and the precision for classifying those who assigned a low score (specificity) was 39.5%. Scheme 8 shows the grouping of tourists according to their preference for tourism activities associated with these social resources.

As can be seen, in the Scheme 8 (indicated in red) the tree discriminates according to the valuation of resources associated with social activities in the city, a node that groups the majority of respondents who assigned a high score to this category (28%), corresponding to those who planned a stay longer than 7 days and have invested less than USD 500 or more than USD 1000 per person in this vacation.

Additionally, the following results are presented with respect to the image projected by Cuenca (Scheme 9) and the activities that can be carried out in the destination (Scheme 10).

Scheme 9 shows the existence of affinity (proximity) between the categories used as images of the city, showing a different pattern for the options “Adventure–Acquisition of knowledge” (indicated in red). Scheme 9 reveals the existence of affinity (proximity) between the activities to be carried out in the city, showing a different pattern for the options “Historical Places–Museums” and for “Traditional Agricultural Activities”.

On the other hand, the development of models made it possible to predict, based on the characteristics of the tourists surveyed, recorded in the questionnaires, the valuation of the resources associated with “Interaction with Nature” with 85% accuracy, “Cultural Activities” with 68% accuracy, and “Social Interaction” with 59% accuracy.

The preference for “Interaction with Nature” stands out in these results, reinforcing the need to create integrated tourism products, which broaden the possibilities of increasing the levels of satisfaction of tourists, in combination of experiences from different areas. These practices not only have a positive impact on the interest of the tourist that shows the ecological practices as a positive influence on the innovative performance of human resources [67], the implementation of community-based tourism allows taking advantage of endogenous resources as an alternative to poverty [68].

According to these models, the highest values assigned by tourists according to category group are:

Resources associated with “Interaction with Nature”: mainly those who expressed interest in doing “Hiking” and are not “University Students”.

Resources associated with “Cultural Activities”: mainly those from “Colombia”, “Hungary”, “Argentina”, “USA”, “Canada”, “Chile”, “Spain”, “Peru”, “Venezuela”, “Italy”, “Russia”, “New Zealand”, “South Africa”, “Ukraine”, “Uruguay”, “Czech Republic”, and “Sweden”, who, in turn, about the activities they would like to do in Cuenca indicated “Historical Places” and did not indicate “Traditional Agricultural Activities”.

Resources associated with “Social Interaction”: mainly those who planned a stay longer than 7 days and invested less than USD 500.00 or more than USD 1000.00 per person in this vacation.

Subjectively, these levels of accuracy are considered “moderate”, especially if one takes into account the cross-cutting nature of the tourists’ evaluation, that is to say, the majority of tourists assigned high scores to most of the categories evaluated. Nevertheless, this model offers a general reference of the profile of tourists for whom each type of tourism resource prevails over the others.

The above information is relevant to consider the activities that can be carried out indistinctly in correspondence with the preference of the market segments, taking into account that the preference for carrying out activities related to “Cultural Activities” is generally seen in tourists from Europe and South America and those who refer to activities related to “Social Interaction” are those who remain in the town for more than 7 days.

Finally, by way of closing the instrument applied for gathering primary information, the opinion of tourists about their visit to Cuenca was evaluated regarding the main positive and negative aspects, and the responses to the open-ended question were coded, classified, and quantified (

Table 2. Most relevant aspects considered by tourists regarding the destination (open question).

Heritage	Answers containing terms: architecture, culture, cathedral, historical center, buildings, museums, churches
Hospitality	Answers containing terms: hospitality, friendliness, respect, people, treatment
Natural resources	Answers containing terms: landscapes, parks, rivers, nature, Cajas
Gastronomy	Responses containing terms: food, gastronomy
Public transportation	Answers containing terms: traffic, transportation, buses, cabs
Cleanliness	Answers containing terms: clean, dirty, pollution, smoke, tidiness, animal waste
Security	Answers containing terms: security, tranquility, repression, police, swindling
Weather	Answers containing terms: climate, cold, weather
Urban organization	Answers containing terms: size of streets, signage, organization, order, information, bureaucracy
Recreation	Answers containing terms: activities, tours, bars, restaurants, events, festivals, entertainment, parties, traditional activities, public spaces
Prices	Answers containing terms: price, cost, economic, expensive
Environment	Answers containing terms: pleasant, quiet, relaxed atmosphere
General	Answers containing terms: beauty, nice, everything
Other	Responses containing terms not expressed in the other categories: camping, markets, indigence, animals, and whose wording expresses liking or disliking

). The processing of these responses made it possible to identify 765 opinions, of which 578 rated the city positively and 187 rated it negatively. Likewise, tourists identified 14 aspects as most relevant, namely:

The following Scheme 10 summarizes the quantification of the opinions of those surveyed regarding what they liked or did not like about the city, showing that between 69.3% and 79.0% of tourists have a positive opinion of the city during their visit.

4.3. Channel Preference Analysis for the Travel Decision

The analysis of these hypotheses contributed to demonstration of the significance that technology has in the decision on the tourist’s destination and its influence on the selection of experiences that may be consistent with their expectations of enjoying their leisure time.

H1. 

Trends in tourism distribution point to the coexistence of traditional channels and the use of information and communication technologies.

H2. 

Trends in tourism distribution point to the prevalence of ICT use.

The results of the descriptive analysis on the availability of access to and use of ICTs for travel information and travel arrangements show that:

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61% stated that they had obtained information about Cuenca in their country of residence (38%) or in Ecuador (23%);

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91% stated that they had obtained information about the destination from sources other than travel agencies;

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89% stated that they had organized their trip through sources other than travel agencies;

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84% stated that they used mobile devices to make inquiries on the Internet;

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69% stated that they had not paid for their trip electronically;

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80% reported a medium–high level of confidence with respect to electronic transactions;

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89% stated that they have not had any bad experiences when making electronic transactions in Ecuador.

The following graphs show these results visually.

Scheme 11 suggests that the sources of information used to obtain information about Cuenca are opposed, with the case of “Travel Agencies or Tour Operators” being the most evident, since affirmative responses to this category are farther away (different) from the remaining patterns. In turn, in the case of the categories “Relatives or Friends” and “ICT”, their affirmative responses are closer to the negative responses of their peers.

Scheme 12 shows proximity among the affirmative responses to all the categories evaluated, suggesting a non-exclusive or combined use of the three channels. Consequently, it is assumed as a finding that a necessary condition for the eventual coexistence between the different tourism distribution channels (physical and virtual) is the concentration by each channel of minimum percentages of tourism demand, since, to the extent that a distribution channel is less used (registers a lower percentage of market share), its probability of remaining and therefore coexisting with other channels in the market decreases.

On this basis, the following were compared as a reference for the levels of coexistence between these channels:

• The estimated percentage of tourists who organized their trip through a travel agency or tour operator in Ecuador versus the estimated percentage who did so through ICT tools.
• The estimated percentage of tourists who obtained information about Cuenca from travel agencies or tour operators in Ecuador versus the estimated percentage who did so through ICT tools.

4.3.1. Comparison of the Estimated Proportion of Tourists Who Organized Their Trip through a Travel Agency or Tour Operator in Ecuador vs. the Estimated Percentage Who Did So through ICT Tools

The “binomial test” available in SPSS was used for this comparison. The variable “X = Proportion of tourists who used travel agencies or tour operators to organize their trip” could be adjusted to a normal distribution. Similarly, the proportion of tourists who used ICT to organize their trip was estimated, which also followed a binomial sampling distribution of parameters, verifying from the goodness of fit that it also corresponds to a normal distribution. In practical terms, this entailed knowing the population variance in order to be able to make the corresponding inferences, for which the “t-Student” statistic was used, which yielded the following results:

• The participation of “Travel Agencies or Tour Operators” and “ICT” are significantly different from 0%.
• The share of “Travel Agencies or Tour Operators” ranged from 7.3% to 13.2%.
• The share of “ICT” ranged between 38.6% and 48.2%.
• The share of “ICT” is significantly higher than that of “Travel Agencies or Tour Operators”.
• The share of “Travel Agencies or Tour Operators” is significantly higher than 5%.

Based on this information it is possible to summarize the following:

It is estimated with a confidence level 1-α = 0.95 that the percentage of tourists using “Travel Agencies or Tour Operators” as a channel to organize their trips ranges between 7.3% and 13.2%, while the participation of “ICT” ranged between 38.6% and 48.2%, the latter being a significantly higher percentage. Likewise, a comparison of these channels as a source of tourism information shows an even greater difference in favor of ICTs.

On the other hand, by applying supervised classification models of the “decision tree”, it was possible to predict the propensity to use ICTs as a tourism distribution channel with 67% accuracy. According to this model, the tourists most likely to use ICT to organize their trip are first those indicated in Group 2, as a result of the segmentation by preferences, in particular those whose main reason for visiting Cuenca was “Culture” or “Nature”, and second those indicated in Group 1, in correspondence with this segmentation, in particular those who associate the city more with concepts of security than of knowledge.

This information indicates that the structuring of tourism products combining nature and culture encourages the creation of multidisciplinary groups to generate agile responses that translate into motivating experiences. Based on these, communication strategies supported by ICT are defined.

Examples of this can be found in the study of Celdrán-Bernabeu, Mazón, and Giner-Sánchez, who demonstrate that the application of open data in tourism can generate innovative ecosystems for the creation of ICT-based products, as well as the low level of use of open data in tourism [56]. Rivera et al. explain the significance of the use of web pages for those regions that receive a strong flow of tourists, especially if the segments served are international tourists, in which case these pages should offer information in several languages [69]. Cruz and Miranda also identified, as variables of use and trust on the part of tourists, technological instruments for the control of capacity and access to the tourist site and support management [70]. However, the studies carried out regarding the use of web pages by intermediary agencies show their inefficiency and lack of preparation to face this challenge. An SEO analysis shows that the expressions in relation to tourism are irrelevant and, on the other hand, their positioning is weak: only international agencies use keywords that correspond to their (international) market, as dual companies, wholesalers, and operators. they are not oriented to their objective segments [71]. From another perspective, Padilla, Parra and Beltran [72] carry out a study of the evolution regarding the implementation of web 2.0, in a region, reaching the conclusion that large companies have passed this stage by using the web 3.0, although they have not yet reached their optimal use, while lower category hotel companies have managed to position themselves with web 2.0.

Faced with the COVID-19 crisis, recreational farm tourism entrepreneurs implemented computerization and cost control strategies in response to market demands [73].

An SEO analysis shows that the expressions related to tourism are irrelevant and, on the other hand, their positioning is weak: only international agencies use keywords that correspond to their (international) market, while dual companies, wholesalers, and operators are not oriented to their target segments [64].

From another perspective, Prada and Pesántez carried out a study of the evolution regarding the implementation of Web 2.0 in a region, reaching the conclusion that large companies have passed this stage by using Web 3.0, although they have not yet reached optimal use, while lower-category hotel companies have managed to position themselves with Web 2.0 [65].

4.3.2. Comparison of the Estimated Proportion of Tourists who Obtained Information about Cuenca through Travel Agency or Tour Operator vs. Those Who Used ICT Tools

The development of this point is based on the same assumptions and procedures of the previous section, which are applied to the categorical variables:

• Proportion of tourists who selected “Catalog of a travel agency or tour operator in my country”.
• Proportion of tourists who selected “ICT options (Internet, mobile applications, or websites)”.
  A t-test yielded that:
• The share of “ICT” is significantly higher than that of “Travel Agencies or Tour Operators”: the share of “Travel Agencies or Tour Operators” ranged from 5.0% to 10.1%; the share of “ICT” ranged from 51.9% to 61.5%.

4.3.3. Propensity to Use Different Tourism Distribution Channels

As part of the diagnosis on the use of the different tourism distribution channels (in particular “Travel Agencies or Tour Operators” and “ICT”), it was evaluated whether, according to their responses, it was possible to predict the propensity of respondents to use any of these channels, understanding “use” as obtaining information about Cuenca or organizing the trip.

The results of the various model runs performed showed the following:

• In general terms, the models failed to individually predict the propensity to use travel agencies or tour operators as a tourism distribution channel, suggesting that the use of this distribution channel is not necessarily associated with a specific profile of tourists identifiable from the questionnaire.
• In the case of the propensity to use ICT, the models were able to predict it (individually and globally) with an average accuracy of 0.61. In informal terms this means that, approximately, out of every 100 individuals evaluated, the models correctly predict the tourism distribution channel used by 61.
• The best performing model predicts the propensity to use ICT tools for travel arrangements, with an overall accuracy of 67.4%, according to the results indicated in the confusion matrix of the test set. The accuracy for classifying the observations corresponding to tourists who used ICTs (sensitivity) was 46.7% and the accuracy for classifying those who did not use ICTs (specificity) was 88.6%.

The results of the model are shown in Scheme 13 (Indicated in red those of less significance).

According to these results, the profiles of people with the highest propensity to use ICTs to obtain information about Cuenca are:

• Those in the unsupervised segmentation classified in Node 2 (mainly Europeans with no intention of settling in Cuenca), whose main reason for visiting Cuenca was “Culture” or “Nature”.
• Those who in the unsupervised segmentation were classified in Node 1 (mainly North Americans with the intention of settling in Cuenca), who associate the city more with concepts of security than knowledge.

5. Conclusions

In response to the first research question, the study contributed to the knowledge dimensions of the tourism value chain and technology as an essential component, determining a new structure, which takes as fundamental factors the significance of innovation and the incorporation of new technologies in small tourism businesses, within the scope of the local destination, evidencing the need to value existing knowledge in territories with a tourist vocation. This led to a proposal for the formulation of the chain, which assumes that technology and knowledge management constitute a transversal axis, present in all phases of the management of the tourist product, from the integrated approach of the offer. This presupposes the connection of attributes derived from the existing resources/attractions in the locality, to raise the level of satisfaction of tourists from the perspective of an integrated experience.

The changes in demand that tourism has been experiencing as a trend since the beginning of the 21st century have led to structural imbalances such as seasonality, territorial concentration, and poor diversification of supply. This implies the need to structure an offer for different types of market segments; each one of them with different expectations, whose satisfaction depends on the offer of unique and innovative products in an integrated conception of the territory, aiming at the unique and differentiated value capable of sustaining its positioning in the market [74].

Taking into account the role of innovation and ICT within the framework of the indicated trends, the empirical study demonstrates the hypothesis about the prevalence of technology use by tourists at the time of deciding their trip. This gives greater significance to the need of using of info-communication technologies based on data mining, which makes it possible to manage information and knowledge effectively, by bringing to the forefront the needs and desires of tourists, based on the value they place on the resources/attractions that the territories possess in correspondence with their expectations when visiting the destination.

This is reaffirmed by the development of models that made it possible to predict with 67% accuracy the selection of ICTs as a distribution channel for travel arrangements based on the characteristics (of tourists) recorded in the questionnaires; however, studies conducted on the use of web pages by intermediary agencies show their inefficiency and lack of preparation to meet this challenge.

Based on the previous assumptions, it is possible to design products consistent with such expectations, incorporating into a project the knowledge of the members of the community, taking advantage of the existing potential in small businesses that manage tourism at the local level, their experience, and creativity, which are strong drivers of innovation. Combined with the incorporation of new technologies, these decide the rest of the components of the value chain of the destination. That is to say that elements are necessary to meet these expectations from the perspective of the complementary products that make up the tourism offer and to know what prices can be more competitive, how to distribute this offer according to the usage options of the different segments, and how to communicate using technological means and the different technological marketing tools.

To this end, the results obtained in the research on the tourist profile (based on the structured questionnaire applied to a random sample of 419 tourists who visit the city of Cuenca, Ecuador, selected as a case study) can be taken as a basis. The analysis of the variables and their measurement reveal a high level of appreciation of the city’s tourist resources/attractions (average greater than 3 in 10 of the 11 categories evaluated). In addition, it corroborates that the main reason for travel is associated with historical–cultural resources/attractions.

With respect to demand, the US continues to be the first country that sends tourists to the city, coinciding with the statistics that place it as one of the main locations at the country level after Colombia. Argentina, Canada, Colombia, Spain, and Mexico occupy second place, coinciding with other demand studies carried out in the city [65,75].

It is important to pay attention to the fact that the use of technology in the management of tourism supply remains as a significant element regarding human interaction and its relationship with the exchange processes, because it turns people into authentic protagonists of the demand and consumption of information. Unidirectional communication becomes bidirectional and in it the consumer assumes a leading role, supported by mobile devices, e-mail habits, navigation, and social networks.

The above allows inferring that in this way behaviors are developed that create a new lifestyle in which more and more access facilities are demanded, that is to say, a culture sustained by new technologies is created. If a few years ago there were talk of multimedia and interactivity, now the key words are convergence and transmedia, connecting media through relevant stories [76]. New technologies have changed the way tourists plan their travel experience [77].

In summary, the results of the study contribute to the foundation of decisions based on knowledge management. It means the conversion of this information into support for the management of tourism in the locality, bringing to the fore the need to incorporate the use of technologies in the improvement of the value chain.

Future Lines of Research and Limitations of the Study

The findings of the research point to the need for continuity in the following key lines or questions:

• What factors, in addition to those identified, could help the city of Cuenca move towards a smart tourism destination, as an alternative, to consolidate its value chain?
• What alternative financing channels could be used to generate greater investment in the use of technological resources for tourism purposes?
• What alliances could be encouraged on the part of the stakeholders, based on the use of these tools, to make them more useful and increase their effectiveness, and how could this be carried out?
• What indicators can be used to measure the impact of the use of these technological tools, to encourage their presence as a coordinating entity for tourism stakeholders and make it possible to improve the chain?
• What level of generalization could the results and conclusions obtained have, by extending the scope of the study to other similar cases both in Ecuador and internationally, with which comparative studies could be carried out and the variations caused by the COVID-19 pandemic could be incorporated?

Finally, the authors recognize the following as the main limitations of the study, especially at the theoretical, methodological, and practical levels:

• The non-application of pilot tests in the definition of the optimal categories to be included in the final questionnaire, according to the objectives of the research.
• The non-definition, in all cases, of categories to minimize the possibility of ambiguous interpretations by the interviewee and whose meaning is exclusive with respect to the other categories.