The importance of the distribution of accommodation businesses over a certain area has grown remarkably, especially if such distribution is mapped using tools and techniques that utilize the territory as a variable in the analysis. The purpose of this paper is to demonstrate, by means of a geographical information system (GIS) and spatial statistics, that it is possible to better define the groupings of rural accommodation available in Extremadura, Spain, especially if these are conceptualized by dint of their lodging capacity. To do so, two specific techniques have been used: hotspot analysis and outlier analysis, which yield results that prove the existence of homogeneous and heterogeneous groups of accommodation businesses, based not only on their spatial proximity but also on their lodging capacity. On the basis of this analysis, the regional administration can devise tourist policies and strategic plans in order to improve the management and efficiency of each business. Despite the applicability of the present results, this study also addresses the difficulties in using these techniques—Where establishing the spatial relationships and the boundary distance are key concepts. In the case study here, the ideal configuration utilizes a fixed distance of six miles.

Artificial intelligence (AI) is profoundly transforming heritage tourism through the incorporation of technological solutions that reconfigure the ways in which cultural heritage is conserved, interpreted, and experienced. This article presents a critical and systematic review of current AI applications in this field, with a special focus on their impact on destination management, the personalization of tourist experiences, universal accessibility, and the preservation of both tangible and intangible assets. Based on an analysis of the scientific literature and international use cases, key technologies such as machine learning, computer vision, generative models, and recommendation systems are identified. These tools enable everything from the virtual reconstruction of historical sites to the development of intelligent cultural assistants and adaptive tours, improving the visitor experience and promoting inclusion. This study also examines the main ethical, technical, and epistemological challenges associated with this transformation, including algorithmic surveillance, data protection, interoperability between platforms, the digital divide, and the reconfiguration of heritage knowledge production processes. In conclusion, this study argues that AI, when implemented in accordance with principles of responsibility, sustainability, and cultural sensitivity, can serve as a strategic instrument for ensuring the accessibility, representativeness, and social relevance of cultural heritage in the digital age. However, its effective integration necessitates the development of sector-specific ethical frameworks, inclusive governance models, and sustainable technological implementation strategies that promote equity, community participation, and long-term viability. Furthermore, this article highlights the need for empirical research to assess the actual impact of these technologies and for the creation of indicators to evaluate their effectiveness, fairness, and contribution to the Sustainable Development Goals.

Evaluating the resources in a tourism destination is one of the previous tasks in the development of its comprehensive planning. There are many criteria to use in order to evaluate tourism resources; but, independently on the number of attributes considered the fact is that not every criterion is equally important in the process of evaluation and ranking of the tourism potential of a destination's resources. In contrast to other well-known methodologies, the aim of this paper is to propose a methodology to weight qualitative and hierarchical evaluation attributes by estimating a discrimination parameter. In this research, an item response theory (IRT) model is used, the graded response model, to estimate each attribute's discrimination coefficient. This parameter will be the basis to propose a weighting system for the entire set of attributes. Graded response model (GRM) will also allow establishing a hierarchy of resources by constructing a continuous latent scale, where it will be possible to position every analysed resource in the tourism destination. The applicability and robustness of the IRT methodology will be tested using data from rural tourism resources in the Spanish province of Cáceres.

Areas with low levels of transformation are alternative destinations for tourists who prefer to visit nonmassified places and have singular experiences. The benefits of these microdestinations are their local populations, traditional products, landscapes, and heritage, which, in turn, allow the cultural and gastronomic roots to be witnessed. Based on this assumption, the present research investigated landscape preferences in the Tejo/Tajo International Transboundary Biosphere Reserve (Portugal/Spain), where Dehesa/Montado and traditional olive groves play important economic and sociocultural roles. This investigation sought to compare the opinions of those who live there with those who visit the territory in terms of landscape and agritourism experience preferences. To this, 439 interviews were conducted, and the results were extracted through descriptive analysis techniques and parametric and nonparametric tests to understand the different opinions. The main results were that agricultural landscapes are among the most preferred, and visitors tend to give the landscape higher scores, while the local population has some ignorance of its potential. The potential of agritourism was revealed through the motivation expressed by the demand to participate in gastronomic experiences and have contact with local products, followed by participation in activities that allow people to enjoy the agricultural landscape and rural traditions. The results revealed that the agritourism concept is often confused with rural tourism and nature tourism. Thus, it is necessary to develop a strategy to support the tourism supply according to the concept of authentic agritourism. In this way, agricultural activity has an important role in driving sustainable tourism dynamics in cross-border regions and boosting new products based on the culture, nature, and biodiversity characteristics of a protected area.

Dehesas form an agroforestry system which is highly developed in Extremadura as they occupy over 1,000,000 hectares. This is an extensive production system based on exploitation by stockbreeding with certain complements of agricultural and extractive products. It is however underexploited for activities other than agrolivestock production. As a result this research starts from the hypothesis that greater socio-economic development is possible in areas near this type of ecosystem if we consider that it is extremely attractive to tourism, at least in some of its forms. Complementing agrolivestock exploitation with tourist exploitation means that it is necessary to be familiar with the situation of the current availability of accommodation. In order to do so we analyse the main parameters characterising rural accommodation in Extremadura, Spain, the results of which reflect low occupancy for a large part of the year and consequently seasonal variation is high. This fact contrasts with the huge potential of dehesas for agritourism. In order to carry out this study we resort to the use of spatial statistics, in particular the grouping analysis. In its configuration we consider the location of the rural accommodation and its proximity to areas of dehesas made up of holm oaks (Quercus ilex) and cork oaks (Quecus suber) together with protected natural spaces, basing ourselves also on proximity to livestock trails and natural swimming pools. The results lead to the creation of 5 homogeneous groups of which 3 correspond to accommodation establishments capable of setting up agritourism and agriecotourism initiatives; this affects 45% of the establishments. However, no current initiatives of this type exist despite the fact that the National Reference Centre for Agritourism is located in Extremadura. From this can be inferred the need for implementing tourist policies to encourage the generating of tourist products specifically intended to exploit the potential of the dehesa as a complement to the current availability of rural accommodation.

The use of natural protected areas has been analyzed abundantly in the relevant literature, although on many occasions these areas are studied from the viewpoint of their role as a tourist destination in themselves, while neglecting their role as a tourist attraction that can be visited from the main destination of their stay. In certain specific areas, as in the case of Extremadura, protected areas are often a complementary destination for visitors who are staying in popular tourist hubs. This study is based on data from 4 different spaces (with different degrees in their status as protected areas) about the flow of tourists they generate at the destination. In light of the data, this paper identifies the 41 towns and villages with the most tourists, later to determine their mobility towards natural protected areas. Information was collected from almost 14,000 surveys that were filled at 52 tourist offices. This information allowed us to map the flow of tourists from their places of stay to the protected areas analyzed here, which resulted in the mapping of relevant networks by means of a Geographic Information System following the criterion of shortest path available. The results here clearly demonstrate that each area has a varying capacity to attract visitors, although in a large proportion of cases, the 60-min isochrone is a boundary beyond which the number of visitors drops significantly.